RU2685967C1 - Method of preliminary transformation of a structured data array containing a linguistic sentence - Google Patents

Abstract

FIELD: computer equipment.SUBSTANCE: invention relates to computer engineering for processing data arrays. Technical result is achieved due to the fact that the method of transforming a structured data array (SDA) comprises a step of forming a first data structure, on which the first SDA data structure is formed, comprising elements of said first data structure, wherein said elements of the first data structure are text elements (TE) of the linguistic sentence, as well as identification data of TE, which are for each TE, at least: value of TE and TE serial number in linguistic proposal; and a step of forming a second data structure, on which a second SDA data structure is formed, comprising elements of said second data structure, wherein said elements of the second data structure are syntax units (SU) of the linguistic sentence, formed based on information from the database of linguistic features (DLF) of text elements of the linguistic sentence, and also represent SU identification data.EFFECT: technical result consists in improvement of accuracy of preliminary processing of text in natural language.21 cl, 45 dwg

Description

[1] TECHNICAL FIELD TO WHICH INVENTION RELATES.

[2] The group of inventions relates to solutions in the field of processing data arrays, in particular, to solutions in the field of processing structured data arrays containing text in natural language, in particular, linguistic sentences, and can be used to pre-convert a structured data array to provide its subsequent processing.

[3] LEVEL OF TECHNOLOGY

[4] From the patent of the Russian Federation 2399959 (CJSC Avikomp Services), published 10.05.2010 (D1), a method of automatic indexing of texts in natural languages is known. The method known from D1 is that the text is segmented electronically into elementary units, identifies stable phrases, forms sentences, identifies semantically significant objects and semantically significant relationships between them, forms for each semantically significant relationship many triads, in which a single triad of the first type corresponds to a relationship established by a semantically significant relationship between two semantically significant objects, each of the triads of the second type corresponds to the value of a specific attribute of one of these semantically significant objects, each of the triads of the third type corresponds to the value of a specific attribute of the semantically meaningful relationship itself, then they index all the semantically meaningful objects connected by semantically significant relations into a set of formed triads, store the formed triads and the resulting indices together with a reference to the source text from which these triads are formed.

[5] However, the method known from D1 does not have sufficient accuracy of indexing elements of text in a natural language, which, in turn, affects the accuracy of subsequent processing of a text in a natural language and the accuracy of searching in a text in a natural language. This is mainly due to the lack of effective preprocessing of text in natural language, which, accordingly, does not allow indexation with sufficient accuracy.

[6] DISCLOSURE OF THE INVENTION

[7] On the basis of this, a technical problem solved by the present invention is the creation of a method and devices and / or systems implementing a method that have an increased efficiency of preprocessing a natural language text for its subsequent indexing and processing.

[8] Accordingly, the technical result achieved when implementing the present invention is to increase the efficiency and accuracy of preprocessing a natural-language text for subsequent indexing and processing.

[9] The technical result is achieved due to the fact that the method for transforming a structured data set (MDC), containing at least a linguistic sentence, performed by a processor of a computer device, is characterized by the following steps: A) forming the first data structure, which forms the first structure data of the DMD containing the elements of the first data structure, and the elements of the first data structure are the textual elements (TE) of the linguistic proposition zheniya and identification data of text elements (TE identification data) representing for each fuel cell, at least: a value of a text element (TEQ value) and the ordinal number of the text element (TE ordinal number) in the linguistic sentence; B) the formation of a database of linguistic features (BDLP), which reveal the linguistic features of the text elements (linguistic signs of TE) of the linguistic sentence, from which form a database that represents the BDLP of text elements of the linguistic sentence; C) forming the second data structure, on which the second data structure of the MDD is formed, containing elements of the said second data structure, said elements of the second data structure being syntactic units (CE) of the linguistic sentence, formed on the basis of information from the BDLP of textual elements of the linguistic sentence, also represent the identification data of syntactic units (the identification data of the CE), representing for each CE at least: the value syntactic unit (CE value) and ordinal (s) number (s) of TE linguistic sentences that make up CE.

[10] Embodiments of the present invention relate to methods, devices, systems, and computer-readable media to ensure the efficiency and accuracy of preprocessing a natural-language text for subsequent indexing and processing.

[11] BRIEF DESCRIPTION OF THE DRAWINGS

[12] Illustrative embodiments of the present invention are described below in detail with reference to the accompanying drawings, which are incorporated herein by reference, and in which:

[13] FIG. 1 depicts an exemplary general scheme for performing the steps of the claimed method 100 for transforming a structured data array containing at least a linguistic sentence that is the initial data structure for the method 100 in question.

[14] FIG. 2 depicts an exemplary general scheme for performing the steps of step 101 of forming the first data structure.

[15] FIG. 3 depicts an exemplary general structure of the original data structure from which the first data structure of a structured data array is formed.

[16] FIG. 4 depicts an exemplary overall structure of the generated first data structure.

[17] FIG. 5 depicts an exemplary general scheme for performing the steps of the step 102 of forming a database of linguistic features, which is a database of linguistic features of the text elements 21 of sentence 11.

[18] FIG. 6 depicts an exemplary general structure of the generated linguistic characteristics database (BDLP), which is the BDLP of textual elements 21 of the linguistic sentence 11.

[19] FIG. 7 depicts an exemplary general scheme for performing the steps of step 103 of forming a second SMD data structure.

[20] FIG. 8 depicts an exemplary general structure of a second structured data structure of a structured data array.

[21] FIG. 9 depicts an exemplary general scheme for performing the steps of step 104 of forming a third data structure of a structured data array.

[22] FIG. 10 depicts an exemplary general structure of the formed third data structure of a structured data array.

[23] FIG. 11 shows an exemplary general scheme for performing step 105 of forming a fourth data structure of a structured data array.

[24] FIG. 12 depicts an exemplary general structure of the fourth structured data structure of a structured data array.

[25] FIG. 13 depicts an exemplary general scheme for performing the steps of the claimed method 200 for converting a structured data array containing at least the syntactic units of the linguistic sentence and the identification data of the syntactic units being the original data structure for the method 200 in question.

[26] FIG. 14 depicts an exemplary general scheme for the execution of the identification step 201 for converting a data structure containing syntactic units, which is the initial data structure for the method 200 under consideration.

[27] FIG. 15 illustrates an exemplary overall data structure that is the original data structure for the transform method 200, which is a translatable data structure containing syntactic units.

[28] FIG. 16 depicts an exemplary general scheme for performing the steps of step 202 of forming a fifth data structure of a structured data array, which is the first data structure for the method 200 in question.

[29] FIG. 17 depicts an exemplary general structure of the linguistic characteristics database (BDLP) formed as part of step 2021, which is the BDLP textual elements 21 of the linguistic sentence 11 contained in the elements 22 of the data structure containing syntax units that can be converted.

[30] FIG. 18 depicts an exemplary general structure of the linguistic characteristics database (BDLP) formed under step 2022, which is the BDLP of textual elements 21 of the linguistic sentence 11 contained in the elements 22 suitable for transforming the data structure containing the CE.

[31] FIG. 19 depicts an exemplary overall structure of the fifth structured data structure of a structured data array, which is the first for the present transformation method 200.

[32] FIG. 20 depicts an exemplary general scheme for performing step 203 of forming a sixth data structure of a structured data array, which is the second data structure for the method 200 in question.

[33] FIG. 21 depicts an exemplary general structure of the linguistic characteristics database (BDLP) formed as part of step 2031, which is the BDLP textual elements 21 of the linguistic sentence 11 contained in the elements 61 of the fifth data structure of a structured data array.

[34] FIG. 22 depicts an exemplary overall structure of the sixth structured data structure of a structured data array that is the second data structure for the present transformation method 200.

[35] FIG. 23 illustrates an exemplary general scheme for performing the steps of step 204 of forming the seventh data structure of a structured data array, which is the third data structure for the method 200 in question.

[36] FIG. 24 depicts an exemplary overall structure of the formed seventh data structure of a structured data array, which is the third data structure for the present transform method 200.

[37] FIG. 25 depicts an exemplary general scheme for performing the steps of the claimed method 300 for converting a structured data array containing at least the basic linguistic entities (OLLO) of the linguistic sentence and the identification data of the OLLO, which is the original data structure for the method 300 in question.

[38] FIG. 26 illustrates an exemplary general scheme for performing step 301 of an identification of a data structure suitable for converting, which contains basic linguistic-logical objects (OLLO), which is the initial data structure for the method 300 in question.

[39] FIG. 27 depicts an exemplary general data structure that is the source for the transformation method 300, which is a convertible data structure containing the main linguistic entities (OLLO).

[40] FIG. 28 depicts an exemplary general scheme for performing the steps of step 302 of forming the eighth data structure of a structured data array, which is the first data structure for the method 300 in question.

[41] FIG. 29 depicts an exemplary general structure of the linguistic attributes database (BDLP) formed within step 3021, which is the BDLP text elements 21 of sentence 11 contained in elements 91 of a data structure containing OLLO that is suitable for converting.

[42] FIG. 30 depicts an exemplary overall structure of the eighth formed data structure of the DMD, which is the first data structure of the DMD for this conversion method 300.

[43] FIG. 31 depicts an exemplary general scheme for performing the steps of step 303 of forming the ninth SMD data structure, which is the second data structure for the considered method 300.

[44] FIG. 32 depicts an exemplary overall structure of the ninth formed MDD data structure, which is the second SMD data structure for the present conversion method 300.

[45] FIG. 33 illustrates an exemplary general scheme for performing the steps of step 304 of forming a tenth SMD data structure, which is the third data structure for the method 300 in question.

[46] FIG. 34 depicts an exemplary general structure of the linguistic attributes database (BDLP) formed within step 3041, which is the BDLP text elements 21 of sentence 11 contained in elements 13 of the ninth SMD data structure.

[47] FIG. 35 depicts an exemplary overall structure of the formed tenth data structure of the DMD, which is the third data structure of the DMD for this conversion method 300.

[48] FIG. 36 depicts an exemplary general scheme for performing the steps of step 305 of forming the eleventh SMD data structure, which is the third MDD data structure for the method 300 in question.

[49] FIG. 37 depicts an exemplary overall structure of the generated eleventh data structure of the DMD, which is the fourth data structure of the DMD for this conversion method 300.

[50] FIG. 38 depicts an exemplary general scheme for performing the steps of the claimed method 400 for converting a SMD containing at least the basic linguistic entities (OLLO) of the linguistic sentence and the identification data of the OLLO, which is the original data structure for the method 400 in question.

[51] FIG. 39 depicts an exemplary general scheme for performing the steps of step 402 of forming the twelfth SMD data structure, which is the first data structure for the method 400 in question.

[52] FIG. 40 depicts an exemplary general structure of the linguistic characteristics database (BDLP) formed under step 4021, which is the BDLP text elements 21 of sentence 11 contained in the elements 91 of the data structure containing the OLLO generated under step 4021.

[53] FIG. 41 depicts an exemplary overall structure of the formed twelfth data structure of the SMD which is the first for the present conversion method 400.

[54] FIG. 42 illustrates an exemplary general scheme for performing the steps of step 403 of forming the thirteenth data structure of the SMD, which is the second data structure for the method 400 in question.

[55] FIG. 43 depicts an exemplary general structure of the linguistic attributes database (BDLP) formed under step 4031, which is the BDLP text elements 21 of sentence 11 contained in elements 17 of the twelfth data structure of the MDD.

[56] FIG. 44 depicts an exemplary overall structure of the formed thirteenth data structure of the SMD, which is the second data structure of the SMD for this transformation method 400.

[57] FIG. 45 depicts an exemplary general system diagram for transforming a structured data array.

[58] the IMPLEMENTATION of the INVENTION

[59] The possible embodiments of the present invention described in this section are presented in non-limiting examples of legal protection applicable to particular embodiments of the present invention, which in all their aspects are intended to be illustrative and not restrictive. Alternative implementations of the present invention, not exceeding the scope of its legal protection, are obvious to those skilled in the art having the usual qualifications for which this invention is intended.

[60] FIG. 1, as an example, but not limited to, a general scheme for performing the steps of the inventive method 100 for transforming a structured data set (MDD) containing at least a linguistic sentence (LP), which is the original data structure for the method in question 100, is depicted. The claimed method 100 MDD transformations containing at least the linguistic sentence are characterized by: performing step 101 of forming the first data structure, which forms the first MDD data structure containing the elements the first data structure, and the first data structure elements are the textual elements (TE) of the linguistic sentence, as well as the identification data of the text elements (the identification data of the TE), for each TE, as an example, but not limited to: the value of the text element (TE value) and the sequence number of the text element (TE sequence number) in the linguistic sentence; the step 102 of forming a database of linguistic features (BDLP), which reveal the linguistic features of textual elements (linguistic features of TE) of the linguistic sentence, which form the database representing the database of linguistic features of textual elements of the linguistic sentence (BDLP of TE linguistic sentence); by performing step 103 of forming a second data structure, in which a second MDD data structure is formed, containing elements of said second data structure, said elements of the second data structure being syntactic units (CE) of a linguistic sentence, formed on the basis of information from BDLP TE linguistic sentence, also represent the identification data of syntactic units (CE identification data), representing for each CE, as an example, but not restrictions: the value of the syntactic unit (CE value) and the ordinal (ordinal) number (s) of the TE linguistic sentence that make up the CE; by performing a step 104 of forming a third data structure, in which a third MDD data structure is formed, containing elements of said third data structure, said elements of a third data structure being linguistic objects (LO) of a linguistic sentence, formed by identifying them with said syntactic units or obtained as a result of the transformation of the mentioned syntactic units, and also represent the identification data of linguistic objects ( dentifikatsionnye data LO), which are each LO, as an example, but not limited to: the value of linguistic object (LO value) and serial (serial) number (s) TE linguistic supply components (components) LO; by performing a step 105 of forming a fourth data structure, in which a fourth data structure of the DMD is formed, containing elements of said fourth data structure, said elements of the fourth data structure being logical entities (LogO) of a linguistic sentence, formed by correlating linguistic and logical objects and identified with said linguistic objects, and also represent the identification data of logical objects (identification LogOn data), representing for each LogO, as an example, but not limitation: the value of the logical object (LogO value) and the ordinal (ordinal) number (s) of the TE of the linguistic sentence constituting (components) of the LogO.

[61] FIG. 2, by way of example, but not limitation, shows the general scheme for performing the steps of step 101 of forming the first data structure. Step 101 is characterized by: performing step 1011 of identifying the original SMD data structure in which elements 11 of the original SMD data structure are identified, which are linguistic sentences 11 (LP 11); performing step 1012 of identifying the elements 21 of the first data structure of the DMD, which identifies the elements 21 of the first data structure of the DMD, which are the textual elements (TE) of the linguistic sentence 11, as well as the identification data of the elements 21, representing for each TE, as an example but not restrictions: the value 211 of the element 21 of the first data structure of the DMD and the sequence number 212 of the element 21 of the first data structure of the SMD, and form the first data structure of the SMD.

[62] FIG. 3, by way of example, but not limitation, shows the general structure of the original data structure from which the first SMD data structure is formed. The source data is a MDD containing elements 11 of the original data structure, which are linguistic sentences (LP). Such an array of data is a set of linguistic sentences 11 relating to any field of activity and for any purpose. Elements 11 have no unique names characterizing them (UN) that have practical use. In the original data structure, elements 11, as an example, but not limitation, may be referred to as “LP1”, “LP2”, “LP3”, “LPn”, where n ≥ 1 is the ordinal number of the element in the linguistic sentence. A linguistic sentence is a grammatically organized combination of words (a set of syntactically related words) with semantic and logical completeness. In addition to words, the LP may contain the following objects: numbers (numbers), punctuation marks and indexes (constructions of letters, numbers, and signs). All the objects listed above are components of LP 11 (components of LP) and in the initial data structure are separate elements prepared in advance and placed in the initial data structure not in the form of a linguistic text, but in the form of a structured array (list, list, and the like) of individual Lp Such preparatory actions can be carried out by any method known in the art and, accordingly, are not further described below.

[63] The identification of the elements 11 of the original data structure in step 1011 is reduced to ensuring the classification of the elements that make up the initial data structure as linguistic sentences (LP 11). In this case, the components of the LP are all numbers (numbers), punctuation marks and indexes (constructions of letters, numbers and signs) contained in the PL and separated from each other by a space.

[64] The original data structure is the result of the many elements 11 identified in step 1011.

[65] FIG. 4, by way of example, but not limitation, the general structure of the first data structure formed is depicted. The first data structure is a MDD containing the elements 21 of the first data structure, which are the text elements (TE 21) of the linguistic sentence 11 and the identification data of the TE. The text elements 21 of the linguistic sentence 11 are absent characterizing their unique names (UN), which have practical use. In the data structure, elements 21, as an example, but not limitation, may be referred to as “TE”, “TE2”, “TE3”, “TEn”, where n ≥ 1 is the sequence number of the element in the linguistic sentence 11. (LP 11) are components of the LP, that is, words, numbers (numbers), punctuation marks or indexes (constructions of letters, numbers and symbols) contained in LP 11 and separated from each other by a space. The textual elements 21 of the linguistic sentence 11 have the identification data of TE, such as, by way of example, but not limitation: the value 211 TE and the sequence number 212 TE. The value of 211 TEs is, by way of example, but not limitation, a set of letters, numbers, and (or) punctuation marks that make up TE. The sequence number 212 TE is the sequence number TE 21 in the linguistic sentence 11.

[66] The formation of the text elements 21 of the first data structure during step 1012 is performed by identifying individual words or groups of words, numbers (numbers) or indices, with the numbers (numbers) or indices not separated by a space, as well as punctuation marks. It is preferable that the last punctuation in the linguistic sentence 11 is not taken into account and is not considered as the text element 21 of the linguistic sentence 11.

[67] The identification of the value 211 of the text element 21 of the first data structure during step 1012 is performed by registering the characters (letters, numbers and / or punctuation marks) of which the text element 21 consists. The identification number 212 of the text element 21 of the first data structure in during step 1012, it is produced by calculating the location of the TE 21 in the linguistic sentence 11. In this case, the first text element 21 in the linguistic sentence 11 is assigned the sequence number “1”, and all subsequent TEs receive a sequence number larger by nitsu than the sequence number of the previous TE 21.

[68] The formation of the first MDD data structure during step 1012 is performed by combining in one data structure the elements 21 of the first MDD data structure, as well as their identification data according to principles and methods known from the prior art, which, respectively, are not described in further detail below.

[69] FIG. 5, by way of example, but not limitation, a general scheme is presented for performing the steps of stage 102 of forming a database of linguistic attributes, which is a database of linguistic signs of text elements 21 of sentence 11. Step 102 is characterized by: performing step 1021 of forming linguistic signs of text elements 21 of sentence 11 , on which for the linguistic analysis of the text element provide the identification data of the element 21 (value 211 and the sequence number 212 TE) and get linguistic ha characteristics of 213 text elements 21 of the linguistic sentence 11, as well as the meanings of the said linguistic characteristics of 2131; performing step 1022 of forming a linguistic attributes database (BDLP), on which BDLP of textual elements 21 of the linguistic sentence 11 is formed. In this case, the linguistic feature of the text element 21 will be all linguistic characteristics 213 obtained with the values of linguistic characteristics for the text element 21 2131.

[70] FIG. 6, by way of example, but not limitation, the general structure of the formed linguistic characteristics database (BDLP) is shown. and semantic characteristics. At the same time, the totality of the values of all the linguistic characteristics of a text element is for each TE 21 of the linguistic sentence 11 its distinctive (unique) linguistic attribute in the linguistic sentence. The morphological characteristics preferably indicate the morphological features of TE 21 of the linguistic sentence 11, which can be classified as an example, but not limited to, by the level of nesting (the genus-species-subspecies). At the same time, the morphological genera of the TE 21 linguistic sentence 11 are preferably a word, a number, punctuation marks, other signs; morphological views - part of speech (for words), type of number (Arabic, Roman), type of punctuation mark (full stop, comma, etc.), type of another sign; morphological subspecies - gender, number, case of parts of speech, and the like (for words), number, binary code, index, and the like (for numbers). Syntactic characteristics preferably indicate a variety of syntactic features of TE 21 linguistic sentence 11, among which the following syntactic characteristics of TE 21 linguistic sentence 11 can be distinguished: syntactic role (predicate, subject, and the like); syntactic parent (syntactic main word); syntactic descendants (syntactically subordinate words); syntactic writing relationship (the presence of another TE, having the same syntactic role and the same syntactic parent). Semantic characteristics preferably indicate the semantic features of TE 21 linguistic sentence 11, among which the following semantic characteristics of TE 21 linguistic sentence 11 can be distinguished: semantic group (a group of words that can be attributed to one class, gender, the type or subspecies of objects or actions of the surrounding world when the signs of the mentioned classes, genus, species or subspecies coincide), semantic status (the semantic meaning of a word or group of words in For example, but not limited to, the “seller’s absence at the consumer’s location”, for example, consists of two elements of the top level of nesting (terms): the first is the “seller’s absence” and the second - “location of the consumer”, which have the following semantic statuses: the first one has the main one (determines the meaning of the term), the second one has the additional one (clarifies the previously defined meaning of the main term)).

[71] The formation of the first part (main) of linguistic characteristics 213 and their meanings 2131 for textual elements 21 of linguistic sentence 11 is preferably carried out at step 1021 by complex linguistic analysis of each textual element 21 of linguistic sentence 11, representing, by way of example but not limitation analysis of TE based on the location of TE in the structure of the sentence, its meaning, type, classification of its mental image and analysis of its links with other textual elements in the sentence. According to the results of a comprehensive analysis, the basic linguistic characteristics 213 are preferably formed and entered at stage 1022 into the BDLP as a list of the first part of linguistic characteristics 213 with the values of these characteristics 2131. For example, but not limited to, one of the linguistic characteristics 213 may be , with a value of 2131 of this linguistic characteristic "subject". Such an analysis can be performed by any method known in the art and, accordingly, is not described in further detail below. For example, without limitation, such an analysis can be performed traditionally by a linguistic specialist, or by using a software algorithm of a linguistic (syntactic) processor. Moreover, in the presence of a sufficient number of examples, it is possible to perform such an analysis with the help of a statistical processor (neural network) using the neural network training technology.

[72] Based on the identified first part (main) linguistic characteristics 213 of textual elements 21 of linguistic sentence 11 and their meanings 2131 ultimately form a database of linguistic features that is BDLP of textual elements 21 of linguistic sentence 11. At the same time, the first part of linguistic characteristics of 213 text elements 21 linguistic sentences 11 and their meanings 2131 forms the unique linguistic features of textual elements 21 of linguistic sentences 11.

[73] FIG. 7, by way of example, but not limitation, shows the general scheme for performing the steps of step 103 of forming a second SMD data structure. Step 103 is characterized by: performing step 1031 of identifying and forming the first elements of the second SMD data structure, which identify and form the elements 31 of the second SMD data structure, as well as the identification data of the elements 31, representing for each element 31, as an example, but not limiting , the value 311 of the element 31 of the second SMD data structure and the ordinal (s) number (s) 312 TE of the linguistic sentence 11 constituting the element 31 (value and ordinal numbers of the TE elements 31); performing step 1032 of forming the second elements of the second SMD data structure, on which the elements 32 of the second SMD data structure are formed, as well as the identification data of the elements 32, representing for each element 32, as an example, but not limitation, the value 321 of the elements 32 of the second data structure SMD and sequence numbers 322 TE of linguistic sentence 11, constituting elements 32 (meaning and sequence numbers of TE elements 32); performing step 1033 of forming the second data structure of the DMD, which forms the second data structure of the DMD by combining the identified elements 31 and 32 and their identification data (values 311, 321 and sequence numbers 312, 322 TE).

[74] FIG. 8, as an example, but not limiting, the general structure of the formed second SMD data structure is depicted. The second SMD data structure is a MDD containing elements 31 and / or elements 32, which are the syntactic units (CE) of the linguistic sentence 11 and the identification data CE, representing for each CE, as an example, but not limited to, the value 311 element 31 and (or) value 321 elements 32, as well as ordinal (s) number (s) 312 and (or) 322 TE 21 linguistic sentences, constituting (making) elements 31 and (or) elements 32. Syntactic units (CE) sentences 11 would prefer There are separate words and groups of words connected by a syntactic link. The CE linguistic sentence 11 has characterizing their unique names (UN CE), which have practical use, as an example, but not limitation: "subject", "predicate", "direct addition" and the like. In the data structure, elements 31 and 32 are referred to as unique names and, by way of example, but not limitation, can be referred to as “UNC n”, where n ≥ 1 is the ordinal index of a unique name element in the linguistic sentence, starting with “1” for each New UN CE, not previously encountered in the linguistic sentence. As an example, but not limitation, to clarify the definition of the ordinal indexes of the elements of a data structure that have a unique name (CE and others, mentioned below), the definition of the ordinal index of a CE CE can be demonstrated as follows. In the proposal: “The buyer is obliged to pay and pick up the paid goods, containers and packaging” there are seven CE four unique names: “subject” - one CE, “predicate” - two CE, “definition” - one CE and “addition” - three CE . The data structure will contain one element “subject”, which will have index “1”, as well as two elements “predicate”, which will have corresponding indices “1” and “2”, with index “1” having that “predicate ", Which has a lower TE sequence number, as well as one element" definition ", which will have an index of" 1 ", as well as three elements of" addition ", which will have the corresponding indices" 1 "," 2 "and" 3 ", moreover, the index "1" will have that "addition", which has a lower sequence number of TE. Further, when the CE is mentioned as an element of the second data structure, it means the CE CE. In their structure, CE can consist of one word or several words. The CE of one word (one text element 21 of sentence 11) is always the element 31, which is the original syntactic object (ISO), that is, the member of the sentence established as a result of the syntax analysis. In the future, at the mention of the element 31 of the second data structure, which is ISO, I mean the UN ISO. At the same time, the members of the proposal can be identified many characteristics that in practice can generate a list of updated members of the proposal. Thus, the ISO list is not a predetermined list, but a variable list, depending on the previously set parameters. The same word (text element 21 of sentence 11) in sentence 11 may be named with a different syntactic unit 31, depending on whether the given text element 21 has sentence 11 of different linguistic characteristics 213 and their meanings 2131, as well as the relevance of individual linguistic characteristics. For example, but not limited to, in identifying an ISO “supplement”, in which some linguistic characteristics 213 of this ISO are not relevant, the ISO “direct addition” and ISO “indirect complement” will be assigned to one unique name of the ISO 31 syntax units. When updating all the linguistic characteristics of ISO 213 as separate syntactic units 31, the ISO “direct complement” and the ISO “indirect complement” will be identified. Syntactic units of several words (several text elements 21 of sentence 11) are sometimes ISO (element 31), and sometimes syntactic structures (element 32). The ISO (element 31) of several words (text elements 21 of sentence 11) are found, in particular, in ISO “predicate”. For example, but not limited to, the ISO “predicate” - “could be fulfilled” - consists of three text elements 21 of sentence 11 because of the linguistic peculiarity of the formation of the predicate, which, in addition to the “completed” verb, can have the auxiliary verb “be” and modality (modal verb) "could." The syntactic construction 32 always consists of several words (text elements 21 of sentence 11) and is a construction of syntactically related ISO (elements 31), as an example, but not limited to, a syntactic construction (UN SC) is a “phrase”, “syntax "(Participial, mixed)," simple sentence "," complex sentence ", etc. In the future, at the mention of the element 32 of the second data structure, which is the syntactic construction (IC), we mean the UNC SC. In practice, in order to solve applied problems, the formation of a wide variety of syntactic structures is possible, while the list and description of syntactic structures can be preset. The list of CE 31 (ISO) and CE 32 (UK), which are to be identified in Proposal 11, is preferably predefined.

[75] The identification or formation of the first element 31 of the second SMD data structure in step 1031 is carried out by comprehensive analysis of the values 2131 of the linguistic characteristics 213 of the text elements 21 of the linguistic sentence 11. The elements 31 of the second MDD data structure that are ISO identifiable (if they consist of one ) or formed (if they consist of several TE) at stage 1031, in fact, they are identified with actual ISO. Relevant ISO is an up-to-date list of ISO with current linguistic characteristics, pre-installed and recorded in the first user database (first PDU), which is thus a database of current syntactic units (CE) containing the current ISO and current IC. Identification and formation (if required) of ISO elements 31 is carried out by comparing the values of 2131 linguistic characteristics 213 of textual elements 21 of linguistic sentence 11 with predefined values of linguistic characteristics of the current ISOs recorded in the linguistic characteristics database (BDLP). If the values of 2131 linguistic characteristics 213 of the text element 21 of the linguistic sentence 11 and the predefined values of the linguistic characteristics of the current ISO match, the identified text element is identified and, if necessary, is formed as the corresponding ISO (element 31). Such a comprehensive analysis can be performed by any method known in the art and, accordingly, is not described in detail below. For example, without limitation, such a complex analysis can be performed traditionally by a specialist-linguist, or using a software algorithm of a linguistic (syntactic) processor. Moreover, in the presence of a sufficient number of examples, it is possible to perform such an analysis with the help of a statistical processor (neural network) using the neural network training technology. The formation of the second element 32 of the second MDD data structure in the framework of step 1032 is carried out by a comprehensive analysis of the values of 2131 linguistic characteristics of 213 text elements that are ISO (elements 31). When identifying the linguistic characteristics of the text elements constituting ISO, which correspond to the description of the syntactic structure (IC) contained in the database of current CE, form IC (elements 32) of the two or more ISO (elements 31) mentioned. Such a comprehensive analysis can be performed by any method known in the art and, accordingly, is not described in detail below. For example, without limitation, such a complex analysis can be performed traditionally by a specialist-linguist, or using a software algorithm of a linguistic (syntactic) processor. Moreover, in the presence of a sufficient number of examples, it is possible to perform such an analysis with the help of a statistical processor (neural network) using the neural network training technology.

[76] The identification of the value and ordinal (ordinal) number (s) of the TE element 31 (ISO) of the second SMD data structure in step 1032 is as follows: the value (s) 211 of the text (text) element (s) 21 of the linguistic sentence 11, the constituent element (s) 31 is identified as the value 311 of the element 31 (ISO), and the ordinal number (s) 212 of the said (mentioned) text (s) element (s) 21 of the linguistic sentence 11 constituting the (constituent) element 31 ID It is referred to as the ordinal (s) number (s) 312 of the text (s) element (s) constituting (s) element 31 (ISO). The value and sequence numbers of the TE element 32 (SC) of the second SMD data structure in step 1032 are identified as follows: the values 211 of the text elements 21 of the linguistic sentence 11 constituting the element 32 are identified as the value 321 elements 32 (SC) and the sequence numbers 212 the above-mentioned text elements 21 of the linguistic sentence 11 constituting the element 32 are identified as the sequence numbers of the text elements 322 constituting the element 32 (UK).

[77] The formation of the second MDD data structure during step 1033 is performed by combining in one data structure the elements 31 of the second MDD data structure and the elements 32 of the second MDD data structure, as well as their identification data according to the principles and methods known from the prior art. further not described in detail.

[78] Identification of linguistic characteristics of TE, constituting elements 31 (ISO) of the second SMD data structure and their values, if necessary, is made by organizing a query in the BDLP, formed during step 102, consisting of identification data of TE, constituting ISO 31, and obtaining values 2131 linguistic characteristics of 213 text elements 21 of the linguistic sentence 11, of which element 31 (ISO) consists. Identification of linguistic characteristics of TE, constituting elements 32 (SC) of the second SMD data structure and their values, if necessary, is done by organizing a query in the BDLP, formed in step 102, consisting of identification data of TE, comprising SC 32, and obtaining values of 2131 linguistic characteristics 213 text elements 21 of the linguistic sentence 11, of which element 32 (UK) is composed. At the same time, as described earlier, the linguistic features of elements 31 (ISO) and 32 (UK) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which elements 31 (ISO) and 32 (UK) consist.

[79] FIG. 9, by way of example, but not limitation, shows the general scheme for performing the steps of step 104 of forming the third SMD data structure. Step 104 is characterized by: performing step 1041 of identifying the first element of the third SMD data structure, which identifies or forms the elements 41 of the third SMD data structure, as well as the identification data of the elements 41, representing for each element 41, as an example, but not limitation, the value 411 of the element 41 of the third SMD data structure and the ordinal number of the linguistic sentence 11 of the TE, constituting the constituent element 41; performing step 1042 of forming the second element of the third SMD data structure on which the elements 42 of the third SMD data structure are formed as well as the identification data of the elements 42, representing for each element 42, as an example, but not limitation, the value 421 of the element 42 of the third SMD data structure and ordinal (s) number (s) 422 TE linguistic sentences 11, constituent (s) element 42; performing step 1043 of forming a third MDD data structure, wherein the third MDD data structure is formed by combining the identified elements 41 and 42 and their identification data.

[80] FIG. 10, as an example, but not limiting, the general structure of the formed third SMD data structure is depicted. The third data structure of the SMD is a SMD containing elements 41 and / or elements 42, which are the linguistic objects (LO) of the linguistic sentence 11 and the identification data of the LO, which for each LO, as an example, but not limitation, is 411 the element 41 and (or) the value 421 of the element 42 (the value of the elements 41 and (or) 42), as well as the ordinal (s) number (s) 412 and (or) 422 text elements 21 of the linguistic sentence constituting (constituting) the element 41 and (or) element 42 (orders of magnitude Number of TE elements of 41 and (or) 42). A linguistic object (LO) is a special syntactic unit (EfE). LO linguistic sentence 11 has characterizing their unique names (UN LO), which have practical use as an example, but not limitation, is: “a simple sentence without homogeneous members and turns”, “first phrase” and the like. In the data structure, elements 41 and 42 are referred to as unique names, by way of example, but not limitation, can be referred to as “UN LU n”, where n ≥ 1 is the ordinal index of the unique name element in the linguistic sentence, starting with “1” for each new UN LO, not previously encountered in the linguistic sentence. In the future, when reference is made to LO as an element of the third data structure or elements 41 and 42 of the third data structure, it is meant UNL. EfE is pre-formed within the framework of the linguo-logical transformation, the result of which is the performance of the correlation of linguistic and logical objects and the conversion of syntactic units of a sentence into an array of logical objects. The linguistic-logical transformation mechanism makes it possible to establish a correlation (relationship) between the logical objects of the sentence and the syntactic units of the sentence based on a previously known idea of the logical model of the sentence (the logical structure of a simple uncomplicated sentence identical to a simple judgment). In the course of forming a table of interrelated (linguistic and logical) objects in each individual case, such EfEs are formed, which are the required linguistic objects (sought LO), which can be identified with the desired logical entities (sought LogO). The desired LO generated in this way can be completely identical to one or several CE (such a sought LO will generate the first linguistic object (the first LO), which is the element 41 of the linguistic sentence 11), or it can be a derived syntactic object obtained by converting one or several CE into an object that will be an object that is identical to the desired LO (such a sought LO will generate a second linguistic object (the second LO), which is the element 42 of the linguistic clause 11). The desired logical objects can be separate logical objects or groups of logical objects that are logical entities and are formed according to the laws of logic (the science of thinking). At the same time, there are basic academic logical entities, as an example, but not limitations, such as "concept", "judgment", "subject of judgment" (what something is affirmed or denied in judgment), "predicate judgment" ( that which is affirmed or denied about the subject of judgment). At the same time, for practical purposes, other logical entities can also be formed that reflect the needs of the current application and are used in the framework of the linguo-logical transformation. For example, without limiting, in a predicate of judgment, separate more functionally homogeneous logical entities can be distinguished than the predicate of judgment itself, namely, “the action of the predicate of judgment”, “the object of the predicate of judgment” and “the circumstances of the predicate of judgment”.

[81] The identification of the element 41 (first LO) of the third SMD data structure under step 1041 is made by analyzing the composition of the sought LO. In this case, the composition of the sought LOs is preset in the form of the CE unique name (CE CE) or the list of CE unique names indicating the method of forming the LO, which, without limitation, can be one of the following ways: identification with the established (several established) CE or conversion of the established (established) CE by the method described earlier. The aforementioned list of sought LOs and methods of generating LO form a second user database (second PBB), which is thus the database of sought LOs, including, among other things, the linguistic characteristics of the textual elements from which the sought LOs are formed. If, as a result of analyzing the composition of a specific LO, it is established that the analyzed LO consists of identified CE (elements 31 or elements 32), then such LO is identified (if identical to one CE) or formed (if identical to several CE) as element 41 of the third SMD data structure . Identified within the framework of the analysis of the composition of linguistic objects, syntactic units (elements 31 or elements 32) of the second data structure of the MDD in accordance with the preset identification parameters or the formation of elements 41 of the third data structure of the DMD are identified with the first LO (first linguistic object (element 41 of the third data structure of the MDD)), due to which the element 41 of the third data structure of the MDD is formed. An additional part of the element 41 of the third SMD data structure may be service parts of speech (prepositions, conjunctions, particles) and punctuation marks between syntax units between the third SMD data structure that are combined within the third data structure of the SMD, set by the user. If, as a result of analyzing the composition of a particular LO, it is determined that the LO analyzed consists of convertible CEs, then such a linguistic object will belong to the elements 42 of the third SMD data structure (second LO) and be formed within step 1042. The formation of an element 42 of the third SMD data structure ( second LO) in the framework of step 1042 is produced by converting CE, previously specified in the description of the desired LO type "second LO" according to a predefined method of conversion to the second PBB. The conversion of CE to the elements 42 of the third SMD data structure is an optional step for the present method of converting a structured data array. This method of transforming a structured data array can be implemented with sufficient efficiency and accuracy even if only the element 41 of the third SMD data structure is identified, provided that all the desired LOs generate only the first LO, which is the element 41 of the linguistic sentence 11.

[82] The identification of the value and ordinal (ordinal) number (s) of TE, element 41 (first LO) of the third SMD data structure as part of step 1041 is as follows: value (values) 311 or 321 elements (elements) 31 or 32 of the linguistic sentence 11, identified (identified) with the element 41 (first LO), is identified as the value 411 of the element 41 (first LO), and the ordinal (ordinal) number (s) 312 or 322 TE elements (s) 31 or 32 of the linguistic sentence 11, identified (identified) with element 41 (first L ) Is identified as a sequential (sequence) number (s) 412 of the text (text) element (s) constituting the (constituent) element 41 (first LO). If element 41 is formed according to the requirements of the second PBB by combining several CE, then values and TE numbers of service parts of speech (prepositions, conjunctions, particles) and punctuation marks are added to the values and TE numbers of element 41 (first LO) of the third data structure of the MDD, between the merged CEs. The identification of the value and ordinal (ordinal) numbers of the TE element 42 (second LO) of the third SMD data structure in step 1042 is performed as follows: the value (values) of the transformed CE (from the element (elements) 31 and (or) 32 linguistic sentences 11), identified (identified) with the element 42 (second LO), identify as the value 421 elements 42 (second LO), and the ordinal (ordinal) number (s) of the transformed CE (from the element (s) 31 and (or) 32 linguistic sentences 11) identified with the the element 42 (second LO) is identified as the ordinal (s) number (s) 422 of the text (s) element (s) constituting (constituting) the element 42 (second LO).

[83] The formation of the third MDD data structure during step 1043 is performed by combining in one data structure the elements 41 of the third MDD data structure and the elements 42 of the third MDD data structure, as well as their identification data according to principles and methods known from the prior art further not described in detail.

[84] Identification of the linguistic characteristics of the TEs that make up the elements 41 (first LO) of the third data structure of the SMD data and their values, if necessary, is made by organizing a request to the BDLP, formed during step 102, consisting of the identification data of the TEs that make up the first LO 41, and getting values of 2131 linguistic characteristics of 213 text elements 21 of the linguistic sentence 11, of which element 41 consists (first LO). The linguistic characteristics of the TEs that make up the elements 42 (second LO) of the third SMD data structure and their values, if necessary, are identified by organizing a query in the BDLP formed during step 102, consisting of the identification data of the TEs that make up the second LO 42, and obtaining 2131 linguistic values characteristics of 213 text elements 21 of the linguistic sentence 11, of which element 42 consists (second LL). At the same time, as described earlier, the linguistic features of elements 41 (first LO) and 42 (second LO) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which the elements 41 (first LO) and 42 ( second LO).

[85] FIG. 11, by way of example, but not limitation, shows the general scheme for executing step 105 of forming the fourth SMD data structure. Step 105 is characterized by the formation of an element of the fourth data structure, in which the elements 51 of the fourth SMD data structure are formed, as well as the identification data of the elements 51, which for each element 51, as an example, but not limitation, the value 511 of the element 51 of the fourth SMD data structure and ordinal (s) number (s) 512 TE linguistic sentences 11, constituting (making) element 51.

[86] FIG. 12, by way of example, but not limitation, the overall structure of the formed fourth SMD data structure is depicted. The fourth data structure of the MDD is a DMD containing elements 51 of the fourth data structure of the MDD, which are logical entities (LogO) of the linguistic sentence 11 and the identification data of LogO, which for each LogO, as an example, but not limitation, the value 511 of the element 51 the fourth data structure of the SMD (the value of the element 51) and the ordinal (s) number (s) of 512 TEs constituting (constituting) the element 51 (serial numbers 512 of the TE element 51). Logical objects (Logo) are logical entities and are formed according to the laws of logic (science of thinking). LogO linguistic sentence 11 has characterizing their unique names (UNLOGO), having practical use, as an example, but not limitation, - “concept”, “judgment”, “subject of judgment” (something about which something is approved or is denied in the judgment), "predicate judgments" (what is approved or denied about the subject of judgment, etc.) In the data structure, the elements 51 are called unique names, as an example, but not limitation, can be referred to as "UN LogO n", where n ≥ 1 - the order index The unique name in the linguistic sentence, starting with "1" for each new UNO LogO, previously not encountered in the linguistic sentence, is an element in the linguistic sentence. Later, when LogO is mentioned as an element of the fourth data structure or the element 51, the fourth data structure means UNL An array of logical objects of a sentence is a different, non-linguistic method of registering the meaning of what is involved in a linguistic sentence. Unlike a linguistic sentence, the meaning of which can be saved only if all the text elements of the sentence are registered in one place (as a single unit of information), an array of logical objects allows storing the same information without loss of meaning in a divided form, in many independent storage locations information (in the form of an array of logical objects). At the same time, the formation of an array of logical objects allows not only to divide a single information into parts, but also to systematically structure these parts for any linguistic sentences transformed within the framework of this method. The possibility of registering and storing logically and systemically structured information in parts opens up new possibilities for highly accurate processing of such information, since in this case the search and analysis of information can technically be conducted not in a single volume of initial information (linguistic sentence), but only in certain logical parts of this information , characteristics and requirements for which correspond to the logical essence and logical subject of search or analysis. As a result, this method of storing information significantly reduces the volume (zone) of search and analysis, which leads to a decrease in time and an increase in the quality (relevance, accuracy) of search and analysis.

[87] the Formation of the element 51 (Logo) of the fourth data structure of the MDD in the framework of step 105 is produced using the third data structure of the MDD containing linguistic objects (LO) and the correlation database of linguistic and logical objects, thus representing the third user database (third PBB). The third PBB is preliminarily formed for the linguo-logical transformation. The third PBB is a list of the necessary logical objects that can be distinguished in the linguistic sentence and into which it can eventually be divided. In addition, the third PBB contains a list of linguistic objects of unique names (UN LO) and descriptions of linguistic objects that assume the unique logical objects of unique names that are identical (UN LogO) under the specified conditions (indicated composition of UN LO (list of CE) and / or specified method transformations of the CE, as well as the specified linguistic characteristics of the mentioned CE). For the formation of the logical object 51, correlated with the selected linguistic object 41 or 42 in the third data structure, a separate LO is selected (from the list of LOs) and using the third PBB, a logical object correlated with the UN LO is detected, as an example, but not limitation , choose from the third data structure of LO with a unique name (UN LO) “the first word combination” (a word combination consisting of a simple sentence without homogeneous members and turnovers (for example, a subject) and all words dependent on it)) and send this UN LO as a request to the third PBD to search for the selected LV LO in the list of unique names of the LOs there. Upon detection of such a LV LO (for example, “the first phrase”), in accordance with the third PBB, the LV of the logical object that is identified with it (in the given example, the LV LogO is the “subject of judgment”). Thus, a logical object (element 51 of the fourth SMD data structure) is formed for the selected linguistic object 41 or 42. The result of the formation of element 51 is the identified UN LogO.

[88] The identification of the value and sequence numbers of the TE element 51 (LogO) of the fourth SMD data structure in step 105 is as follows: the value (values) 211 of the text (text) element (elements) 21 of the linguistic sentence 11 constituting (components) correlated with element 51, element 41 or 42, is identified as the value 511 of element 51 (LogO), and the ordinal number (s) 212 of the said (mentioned) text (text) element (s) 21 of the linguistic sentence 11 constituting (components) correlated with element 51, element 41 or 42 is identified as the ordinal (s) number (s) of the text (s) element (s) 512 constituting (constituting) element 51 (LogO).

[89] The formation of the fourth MDD data structure during step 105 is performed by combining in one data structure the elements 51 of the fourth MDD data structure, as well as their identification data according to principles and methods known from the prior art, which, respectively, are not described in further detail below.

[90] Identification of linguistic characteristics of TEs that make up the elements 51 (LogO) of the fourth data structure of the SMD and their values, if necessary, is produced by organizing a query in the BDLP, formed during step 102, consisting of the identification data of TEs comprising LogO 51, and obtaining 2131 linguistic characteristics of 213 text elements 21 of the linguistic sentence 11, of which element 51 (Logo) consists. At the same time, as described earlier, the linguistic features of elements 51 (LogO) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which the elements 51 (LogO) consist.

[91] Further, after completing step 103 described earlier, in order to improve the accuracy of a subsequent search in a structured dataset, it becomes possible to further convert the MDD containing at least the syntactic units (CE) of the linguistic sentence and their identification data.

[92] FIG. 13, by way of example, but not limitation, shows the general scheme for performing the steps of the claimed method 200 for converting an SMD containing at least the syntactic units (CE) of the linguistic sentence and the identification data of the CE, which is the original data structure for the method 200 in question. The claimed method 200 SMD conversions containing at least CE of the linguistic sentence and the identification data of the CE are characterized by: performing step 201 of identifying a convertible structure data containing the CE, which identifies the data structure of the MD, containing the elements mentioned convertible data structure containing the CE, which is the original data structure of the MD in the framework of this method 200, and referred to the elements suitable for converting the data structure are syntactic units (CE) linguistic sentences and CE identification data; performing step 202 of forming the fifth MDD data structure, which forms the fifth MDD data structure, which is the first MDD data structure in the framework of this method 200, containing elements of the fifth fifth data structure of the MDD, and these elements of the fifth MDD data structure are linguistic-logical units ( LLE) linguistic sentences, identified and formed on the basis of the linguo-logical analysis of syntactic units, and also represent the identification data LLE, p edstavlyayuschie a LLE for each, as an example, but not limited to: the value of LLE and serial (serial) number (s) TE linguistic supply components (components) LLE; performing step 203 of forming the sixth MDD data structure, which forms the sixth MDD data structure, which is the second MDD data structure within the framework of the method 200, containing elements of the sixth SMD structure, and said elements of the sixth MDD data structure are groups of linguistic units ( LLE groups of the linguistic sentence formed on the basis of the LLE syntactic linking scheme in the simple sentence of the original linguistic sentence, and also represent bout identification data groups LLE representing LLE for each group as an example, but not limited to: the value of a group serial numbers and LLE TE linguistic proposal constituting the group LLE; performing step 204 of forming the seventh data structure of the DMD, which forms the seventh data structure of the DMD, which is the final data structure of the MDD data for the considered method 200, containing elements of the said seventh data structure of the MDD, OLLO linguistic sentences are formed from LLE groups by eliminating homogeneity in LLE groups, and also represent the identification data OLLO, representing for each OLLO, as an example, but not limitation: the OLLO value and the ordinal (s) number (s) of the TE language of the linguistic sentence constituting (s) the OLLO.

[93] FIG. 14, by way of example, but not limitation, depicts a general flowchart of identification step 201 for converting a data structure comprising syntactic units (CE), which is the original data structure for method 200 under consideration. CE, which identifies the elements 22 suitable for converting the data structure containing the CE, as well as the identification data of the elements 22, representing for Each element 22, by way of example, but not limitation, is the value 221 of element 22 of a translatable data structure containing the CE and the ordinal number (s) of the 222 TE linguistic sentence 11 constituting the constituent element 22.

[94] FIG. 15, by way of example, but not limitation, depicts a general data structure that is the original data structure for the present mapping method 200, which is a mappable data structure containing syntax units. The original data structure is a MDD containing elements 22 of a data structure suitable for converting, containing CE, representing syntactic units (CE) and CE identification data representing, for each CE, as an example, but not limitation, the value 221 of element 22 suitable to convert a data structure containing CE and ordinal (s) number (s) of 222 TE linguistic sentences that make up (s) CE, which, as an example, but not limitation, were described p it with reference to FIG. 8 of the method 100. Elements 22 of the linguistic sentence 11 have characterizing their unique names (UN), which have practical use, as an example, but not limitation: "subject", "predicate", "direct addition" and the like. In the data structure, elements 22 are referred to as unique names and, by way of example, but not limitation, can be referred to as “UNC n”, where n ≥ 1 is the ordinal index of the unique name element in the linguistic sentence, starting with “1” for each new UN CE, not previously encountered in the linguistic sentence. As mentioned earlier, CE can be of two types: the original syntactic objects (ISO), that is, syntactic units - the members of the sentence identified as a result of the syntactic analysis, and syntactic constructions representing the construction of syntactically related ISO. The elements 22 of the convertible data structure containing the CE are a set of ISO of unique names (UN ISO) of the linguistic sentence 11. The ISO 22 in the convertible data structure containing the CE are individual elements prepared in advance and placed in the convertible a data structure containing CE as a structured array (list, list, and the like) of individual ISOs. Such preparatory actions can be carried out by a specified method known from the prior art or by a method unknown from the prior art, such as the method specified in the description of the method 100, and, accordingly, are not further described.

[95] The identification of the elements 22 of the data structure suitable for conversion, which contains CE during step 201, is reduced to the classification of the elements that comprise the data structure that is suitable for transformation, which contains CE as initial syntactic objects (ISO 22). At the same time, separate ISO 22 have the value 221 and the ordinal number (s) of the 222 TE linguistic sentence, constituting (constituting) syntactic units. The value 221 of ISO 22 is one or more text elements (TE 21) of proposal 11, of which ISO is composed. As a rule, ISO consist of one TE 21, with the exception of some ISO. For example, but not limited to, the ISO “predicate” may consist of three TE 21 - “could be performed.” The ISO “predicate” consists of three textual elements due to the linguistic peculiarity of the formation of the predicate, which, in addition to the verb “completed”, can have the auxiliary verb “to be” and the modality (modal verb) “could”.

[96] The identification of the value 221 of the element 22 (ISO) of a data structure suitable for conversion, containing the CE during step 201, is produced by registering a set of signs ТЭ 21 of sentence 11, constituting (constituting) an element of ISO 22. Identification of ordinal (s) numbers (s) The 222TE that constitutes (constitutes) the element 22 (ISO) of a data structure that is suitable for the conversion that contains the CE during step 201 is produced by registering the ordinal (s) number (s) of said FC according to its (their) location in the linguis nical proposal, provided that the first fuel cell in the linguistic sentence has a serial number "1" and all the subsequent FCs have a serial number greater by one than the sequence number of the previous TE.

[97] A convertible data structure containing CE, which is the source for the present transformation method 200, is ultimately a plurality of elements 22, their values 221 and sequence numbers 222 TEs constituting elements 22 identified in step 201.

[98] The identification of the linguistic characteristics of the TEs that make up the elements 22 (ISO) of the data structure containing the CE that can be converted and, if necessary, is produced by organizing a query into the BDLP, formed during step 102 consisting of the identification data of the TEs comprising ISO 22, and obtaining the values of 2131 linguistic characteristics of 213 text elements 21 of the linguistic sentence 11, of which element 22 consists (ISO). At the same time, as described earlier, the linguistic features of elements 22 (ISO) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which the elements 22 (ISO) consist.

[99] FIG. 16, by way of example, but not limitation, shows a general scheme for performing the steps of step 202 of forming the fifth SMD data structure, which is the first data structure for the method 200 in question. Step 202 is characterized by: performing step 2021 of generating values 2141 of the second part of the linguistic characteristics 214 of text elements constituting the elements 22 of a data structure suitable for converting, containing the CE, on which the values 2141 of the second part of the linguistic characteristics 214 of the text elements 21 are formed, constituting x elements 22 and contribute the findings to the BDLP of textual elements 21 of the linguistic sentence 11, formed during step 102, forming as a result the BDLP of text elements 21 of the linguistic sentence 11, forming during step 2021; by performing step 2022 of forming the values 2231 of the third part of the linguistic characteristics 223 of text elements 21 constituting the elements 22 of a data structure suitable for converting, which contains the CE identifying the types of the element 22 of the convertible data structure containing the CE for which certain values of linguistic characteristics need to be changed the said values are 2231 of the third part of the linguistic characteristics of the 223 text elements 21 that make up the elements 22 and contribute the resulting BDLP text elements 21 of the linguistic sentence 11, formed in step 2021, forming as a result of the BDLP text elements 21 of the linguistic sentence 11, formed in step 2022; performing step 2023 of identifying the elements 61 of the fifth SMD data structure, which identifies and forms the elements 61, the fifth data structure of the SMD, as well as the identification data of the elements 61, representing for each element 61, as an example, but not limitation, the value 611 of element 61 the fifth data structure of the SMD and the ordinal (s) number (s) 612 TE of the linguistic sentence 11 constituting (constituting) the element 61, and form the fifth data structure of the SMD.

[100] FIG. 17, by way of example, but not limitation, shows the general structure of the linguistic characteristics database (BDLP) formed within step 2021, which is the BDLP textual elements 21 of the linguistic sentence 11 contained in the elements 22 suitable for transforming the data structure containing the CE. The BDLP, formed under step 2021, differs from the BDLP, formed under step 102, by the presence of 2141 values of the second part of the linguistic characteristics 214, indicating the syntactic-logical identity of element 22 (ISO). To identify linguistic-logical units (LLE) of a linguistic sentence, it is necessary for all syntactic units of the ISO type (element 22) to verify that their syntactic and logical roles in the linguistic sentence 11 are identical. the presence or absence of ISO 22 identity must be established. ISO 22 will be considered syntactically logical identical if its syntactic and logical roles match, and the score will be It becomes syntactically logical non-identical if the roles mentioned do not match. The syntactic role of ISO 22 is a function of a word in a sentence, which is defined within the framework of the interrelationship of words in a sentence. The syntactical role of ISO 22 defines which sentence a word is and in which it has syntactic relations with other words. The same form of a word can perform different functions, that is, be different members of a sentence. The logical role of ISO 22 is a syntactic role, identified with the logical function of a word in a simple judgment. The type of logical function in a simple judgment is associated with the unique name of a logical object (UN LO), which is an element of a simple judgment to which ISO 22 belongs. Simple judgment is a logical entity that is the primary logical construction of thinking that necessarily contains elements of simple judgment - the subject of judgment (the subject of the world in question) and the predicate of judgment (that which is affirmed or refuted about the subject of judgment). At the same time, the subject of the judgment is one subject of the surrounding world, and the predicate of judgment consists, as a rule, of the action and set of objects that are in a certain relationship with each other, which ultimately performs the function of the predicate of judgment, that is, it explains that affirms or refuted the subject matter of judgment. Therefore, the predicate of judgment can be divided into logical functionally homogeneous parts (logical objects), as an example, but not restrictions, such as the action, object and circumstances of the predicate of judgment. The subject of a judgment mentioned earlier, as well as the action, object and circumstances of the predicate of a judgment can be the unique names of a logical object (UNL), which is an element of a simple judgment. In accordance with the word used (ISO 22) by which the elements of simple judgment are expressed, these words (ISO 22) will have a certain logical function, which, according to the predetermined conditions, may or may not be identified with a certain syntactic role. Thus, it becomes possible to verify the identity of the syntactic and logical roles of individual ISO 22 linguistic sentences 11 and convert ISO 22 into linguistic-logical units (LLE).

[101] The formation of the second part of the linguistic characteristics 214 and their meanings 2141 for the textual elements 21 of the linguistic sentence 11 contained in the elements 22 in order to identify the syntactic-logical identity of ISO 22 at step 2021 is performed by checking the ISO 22 for syntactic and logical roles in the linguistic identity sentence 11. The check is a comparison of the values 2131 of the first part of the linguistic characteristics 213 of the text elements 21 constituting the elements 22 with the predetermined values its specified linguistic features of the text elements 21 constituting ISO 22. Conditions for pre-testing are set, such as, by way of example, but not limitation: lists of pairs of ISO 22 whose syntactic and logical roles may not match, as well as signs of syntactic mismatch and logical roles (some values of the linguistic characteristics of these ISO 22, in the presence of which ISO 22 is identified as ISO 22 with the syntactic and logical roles that do not match). ISO 22, which successfully passes the above mentioned test, is identified as ISO 22 with syntactic and logical role overlap (SL-identical to ISO 22, that is, syntactically-logical to identical ISO). ISO 22, which does not pass the above-mentioned verification due to the fact that their mentioned roles do not match, is identified as ISO 22 with a mismatch of syntactic and logical roles (SL-non-identical ISO 22, that is, syntactic-logical non-identical ISO). For example, but not limited to, ISO in the form of a verb has a syntactic role - “predicate”, and ISO in the form of participle - the syntactic role “agreed definition”. Despite the fact that the syntactic roles of the verb and participle do not coincide, from a logical point of view both the ISO and the other are syntactically head words in the same element of the simple judgment “the action of the predicate judgment”, that is, they have the same logical role. As a result, the ISO in the form of a verb passes the verification of the identity of syntactic and logical roles, since the “verb” is what expresses action. At the same time, ISO in the form of an agreed definition does not pass the test, since “definition” is a sign, not an action. For this reason, as well as with the additional condition that the participle is common (has dependent words - meaningful parts of speech), it is considered that ISO “agreed definition” in the form of participle does not pass the above test and is not identical to ISO 22. The mentioned conditions used To verify the identity of syntactic and logical roles, ISO 22 is pre-recorded in the fourth user database (fourth PDU).

[102] Formed as a result of step 2021, the values 2141 (syntactic-logical identity of ISO 22) of the second part of the linguistic characteristics 214 of the elements 21 constituting ISO 22 of the data structure that contains the CE that can be converted into the BDLP of the text elements 21 of the linguistic sentence 11 within stage 102, thus forming the BDLP of textual elements 21 of the linguistic sentence 11, which is formed within the framework of stage 2021. At the same time, both parts (213 and 214) of the linguistic characteristics of the text elements 21 l ngvisticheskogo proposals 11 and their values (2131 and 2141) form features unique linguistic elements 22.

[103] FIG. 18, by way of example, but not limitation, shows the general structure of the linguistic characteristics database (BDLP) formed within step 2022, which is the BDLP textual elements 21 of the linguistic sentence 11 contained in the elements 22 suitable for transforming the data structure containing the CE. The BDLP formed in step 2022 differs from the BDLP formed in step 2021 by the presence of values 2231 of the third part of linguistic characteristics 223, indicating the type of element 22 (ISO) and the actual values of some linguistic characteristics of 213 text elements constituting element 22 (ISO) . To identify linguistic-logical units (LLE) of a linguistic 11, it is necessary for all ISO 22 syntax units, which were checked for the identity of their syntactic and logical roles, to additionally identify the ISO 22 types based on changes in their linguistic characteristics 213 in accordance with their 2141 syntactic-logical identity value 214. As a result of the check for the syntactic-logical identity of ISO 22 carried out at step 2021, it was established that all ISO 22 section According to this feature, SL-identical and SL-non-identical ISO 22. Herewith, SL-non-identical ISO 22 can be changeable and unchangeable, that is, such SL-non-identical ISO 22, in which the values of 2131 should be changed according to a predetermined condition. Some linguistic characteristics are 213 or unchanged. In addition, in some cases, in predetermined conditions, there may be a requirement to create a duplicate of the SL-non-identical ISO 22, which does not change the linguistic characteristics. The above conditions and requirements are set forth in the fourth PBB.

[104] The formation of the third part of the linguistic characteristics 223 and their meanings 2231 for the textual elements 21 of the linguistic sentence 11 contained in the elements 22 is carried out at step 2022 in order to identify various types of ISO 22 based on the syntactic-logical identity (SL-identity) and the formation of a duplicate SL-non-identical ISO 22 through a comprehensive analysis of the conditions established in the fourth PBB, and based on the results of testing ISO 22 on the SL-identity. As a result of the above analysis, for each ISO 22 a specific type is established - the first, second or third type. If, under the conditions established in the fourth PBB, there is a requirement to create a duplicate SL-non-identical ISO 22, then such ISO 22 refers to the fourth ISO 22 type. In accordance with the established ISO 22 form, the values 2231 of the third part of the linguistic characteristics of the 223 textual elements 21 of the linguistic Proposals 11 contained in elements 22. The first type of ISO 22 (SL-identical) contains all their original values 221 and the numbers of text elements 222, as well as their linguistic characteristics 213 and 214 with values 2131 and 2141. In this regard, cheniya 2231 linguistic characteristics of the ISO 213 22 no. In the second type of ISO 22 (SL-non-identical variable), their original value 221 and the number of text elements 222, as well as the second part of their linguistic characteristics 214 with values of 2141, remain unchanged, but the values 2131 of some linguistic characteristics of 213 of the first part change. In this regard, the values of 2231 linguistic characteristics 223 instead of the changing values 2131 of some linguistic characteristics 213 of such ISO 22 are indicated as specified in the fourth PBB. The third type of ISO 22 (SL-non-identical immutable) retains all their original values 221 and the numbers of text elements 222, as well as their linguistic characteristics 213 and 214 with values 2111 and 2141. In this regard, the values 2231 of linguistic characteristics 213 for such ISO 22 are missing. The fourth type of ISO 22 (duplicate SL-non-identical unchangeable ISO) remains their original value 221 and the number of text elements 222, as well as the second part of their linguistic characteristics 214 with values of 2141, but the values of 2131 change some of the linguistic characteristics of the first part. In this regard, the values of 2231 linguistic characteristics 223 instead of variable values 2131 of some linguistic characteristics 213 of such ISO 22 are indicated as specified in the fourth PBB.

[105] Formed at the end of step 2022, the values of 2231 (modified values of linguistic characteristics of ISO 22) of the third part of the linguistic characteristics of 223 elements 21, constituting ISO 22 of a suitable data structure containing CE, are inserted into BDLP of text elements 21 of linguistic sentence 11, formed in as part of step 2021, thus forming the BDLP of textual elements 21 of the linguistic sentence 11, which is formed in the framework of step 2022. All three parts (213, 214 and 223) of the linguistic characteristics of the textual elements s 21 and 11 offers linguistic values (2131, 2141 and 2231) form features unique linguistic element 22.

[106] FIG. 19 shows, by way of example, but not limitation, the general structure of the formed fifth MDD data structure, which is the first for this conversion method 200. The fifth MDD data structure is a MDD containing elements 61 of the fifth MDD data structure, which are linguistic units. (LLE 61) of the linguistic sentence 11 and the identification data of the LLE 61, which for each LLE, as an example, but not limited to, the value 611 of the element 61 of the fifth data structure and ordinal (ordinal f) the number (s) of 612 TEs constituting (components) of LLE 61. LLE 61 of the linguistic sentence 11 has characterizing their unique names (UN LLE), which have practical use as an example, but not limitation: "subject", "predicate" , "Direct addition" and the like. In the data structure, the elements 61 are referred to as unique names, and, by way of example, but not limitation, can be referred to as “UNLLE n”, where n ≥ 1 is the ordinal index of the element of the unique name in the linguistic sentence, starting with “1” for each new UN LLE, not previously encountered in the linguistic sentence. A linguistic-logical unit (LLE 61) is a syntactic unit of the ISO type, according to which a check is made for the identity of its syntactic and logical roles in the linguistic sentence. There can be two types of LLE 61: the first type is the original ISO 22, which passed the mentioned test, which was contained in the data structure containing the CE that is suitable for conversion, and the second type is a duplicate of the ISO 22, which was not in the mentioned data structure. The first LLE 61 type corresponds to all ISO 22 suitable for converting a data structure containing CE. The second type of LLE 61 corresponds to those of ISO 22 suitable for transformation of a data structure containing CE, which are assigned to the fourth type (duplicate SL-non-identical unchanged ISO) specified in the value of 2231 of the third part of linguistic characteristics 223.

[107] The identification and formation of the elements 61 of the fifth SMD data structure during step 2023 is made based on the results of step 2022 for identifying the types of elements 22 suitable for transforming the data structure containing the CE. The identification of elements 61 (LLE) of the first type at step 2023 is made by identifying them with elements 22 (ISO) of the first, second and third types. ISO 22, identified at stage 2022 as the fourth type, forms new elements — elements 61 of the second type of the fifth SMD data structure. The formation of the elements 61 (LLE) of the second type at step 2023 is carried out by identifying them with the elements 22 (ISO) of the fourth type.

[108] The identification of the value and ordinal (ordinal) number (s) of the TE element 61 of the first type of the fifth SMD data structure identified with the first type of ISO 22 is produced in step 2023 by identifying the value 611 of the element 61 with the value 221 of the first type 22 and the ordinal (s) number (s) of 612 TEs constituting (constituting) element 61, by identifying with the ordinal (ordinal) number (s) of 222 TEs constituting (constituting) element 22 of the first type. Identification of the value and ordinal (s) numbers (numbers) of the TE element 61 of the first type of the fifth SMD data structure identified with the second type of ISO 22 is produced in step 2023 by identifying the value 611 of the element 61 with the value 221 of the second type 22, and ordinal ( serial) numbers (numbers) 612ТЭ, making an element 61, with serial (serial) numbers 222 ТЭ, making (making) an element 22 of the second kind. Identification of the value and ordinal (s) numbers (numbers) of the TE element 61 of the first type of the fifth SMD data structure identified with the third type of ISO 22 is produced in step 2023 by identifying the value 611 of the element 61 with the value 221 of the third type 22, and ordinal ( ordinal numbers (numbers) 612 of text elements 21 constituting element 61, with ordinal (ordinal) number (numbers) of 222 TE constituting (constituting) element 22 of the third type. The identification of the value and ordinal (s) numbers (numbers) of the TE element 61 of the second type of the fifth SMD data structure identified with the fourth type of ISO 22 is performed in step 2023 by identifying the value 611 of the element 61 with the value 221 of the third type 22, and ordinal ( ordinal numbers (numbers) of 612TE constituting (constituting) element 61, with ordinal (ordinal) number (numbers) of 222 TE constituting (constituting) element 22 of the third type.

[109] The formation of the fifth MDD data structure during step 2023 is performed by combining in one data structure elements 61 of the first and second types of the fifth MDD data structure and their identification data according to principles and methods known from the prior art, which, respectively, are not further described in detail .

[110] Identification of linguistic characteristics of TEs that make up the first or second elements 61 (LLE) of the fifth SMD data structure, and their values, if necessary, is made by organizing a request to the BDLP, formed as part of step 2022, consisting of the identification data of TEs that are first or second element 61 (LLE), and obtaining the values (2131, 2141, 2231) of all parts of the linguistic characteristics (213, 214, 223) of the text elements 21 of the linguistic sentence 11, of which the first or second element 61 (LLE) consists. At the same time, as described earlier, the linguistic features of the first and second elements 61 (LLE) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which the elements 61 (LLE) consist.

[111] FIG. 20, by way of example, but not limitation, shows the general scheme for performing step 203 of forming the sixth SMD data structure, which is the second data structure for the method 200 under consideration. the elements 61 of the fifth MDD data structure, on which the values 2151 of the fourth part of the linguistic characteristics 215 of the text elements 21 constituting the elements 61 are formed, and which are derived from SIC BDLP in the text linguistic elements 21 Proposition 11 that is generated in phase in 2022, forming eventually BDLP text elements 21 linguistic Proposition 11, formed in 2031 under the stage; performing step 2032 of forming elements of the sixth SMD data structure on which elements 71 of the sixth SMD data structure are formed, as well as identification data of the elements 71, representing for each element 71, as an example, but not limitation, the value 711 of element 71 of the sixth SMD data structure and ordinal (s) number (s) 712 TE of the linguistic sentence 11, constituting (making) element 71; and form the sixth data structure MDD.

[112] FIG. 21, by way of example, but not limitation, shows the general structure of the linguistic characteristics database (BDLP) formed within step 2031, which is the BDLP text elements 21 of the linguistic sentence 11 contained in the elements 61 of the fifth UDF data structure. The BDLP formed in step 2031 differs from the BDLP formed in step 2022 by the presence of 2151 fourth-part linguistic characteristics 215 indicating the level of syntactic significance of element 61 (LLE). The level of syntactic significance of the element 61 (LLE) characterizes the location of LLE in the syntactic tree of the linguistic sentence 11. The syntactic tree is the syntax of the sentence of sentence 11, in which a separate syntactic connection is established between the individual words (LLE). Depending on the composition and structure of the sentence, the syntactic tree may contain an indefinite number of syntactic levels and parts of the sentence that contain the main logical elements (the subject and the predicate of the judgment). The syntax tree used in this method contains elements (LLE) of at least three levels of syntactic significance (HSS). The first HSS include LLE, located on the syntax vertex of the syntactic tree. The second HSS include LLE, which are direct syntactic descendants of syntactic vertices. The third HSS include all other LLE linguistic sentences. A syntactic vertex is a syntactic unit (LLE), having a predicate role. A feature of LLE "predicate" is that it can consist of three words. A direct syntactic descendant of a syntactic vertex is a syntactic unit (LLE), which has a direct subordinate connection with the word of the LLE group of the first level. The establishment of the syntactic level of LLE is the syntactic structuring of LLE.

[113] The formation of the fourth part of the linguistic characteristics 215 and their meanings 2151 for the textual elements 21 of the linguistic sentence 11 contained in the elements 61, in order to establish the level of syntactic significance of the elements 61 of the fifth SMD data structure during step 2031 is produced based on a comprehensive analysis of the values of linguistic characteristics all LLE 61 linguistic sentences, on the basis of which form the syntactic tree of the linguistic sentence. As a result of finding out the position of each LLE in the syntactic tree of a sentence, they determine the level of syntactic significance of each LLE 61.

[114] Formed at the end of step 2031, the values of 2151 (the syntactic significance level of LLE 61) of the fourth part of the linguistic characteristics 215 elements 21 constituting the elements 61 of the fifth SMD data structure contribute to the BDLP of textual elements 21 of the linguistic sentence 11 formed in BDLP text elements 21 of the linguistic sentence 11, formed in the framework of step 2031. In this case, all parts (211, 214, 223, 215) of the linguistic characteristics of the text elements 21 of the linguistic sentence 11 and their meaning (2111, 2141, 2231, 2151) form the unique linguistic features of the elements 61.

[115] FIG. 22 shows, by way of example, but not limitation, the general structure of the sixth formed data structure of the SMD, which is the second data structure for this transformation method 200. The sixth data structure of the MDD is the SMD containing elements 71, which are structured groups of linguistic units. (LLE groups) of the linguistic sentence 11 and the identification data of the LLE groups, representing for each LLE group, as an example, but not limitation, the value 711 of the element 71 of the sixth pattern data courses and ordinal (s) number (s) of 712 TEs constituting (constituting) the LLE group. The LLE 71 groups of the linguistic sentence 11 lack the unique names that characterize them (UN LLE groups) that have practical use. In the data structure, elements 71, as an example, but not limitation, may be referred to as “LLE 1 group”, “LLE 2 group”, “LLE 3 group”, “LLE n group”, where n ≥ 1 is the element number in linguistic sentence. The LLE group of a linguistic sentence 11 is syntactic units of the “syntactic structure” type, which are formed from linguistic-logical units (elements 61 of the fifth SMD data structure) of different levels of syntactic significance of the LLE. The first LLE group (first elements 71 of the sixth SMD data structure) includes both the main LLE of the first LLE group, which are the mentioned syntax vertices (LLE of the first HSS), and the other LLE of the first LLE group (group 1 LLE), which are consistently subordinate to LLE, the first of which has a direct subordinate connection with the LLE of the first HSS, up to the LLE, which is the main LLE of the second group of LLE. The second LLE group (the second elements 71 of the sixth SMD data structure) is referred to as the main LLE of the second LLE group, referred to as the LLE of the second HSS, provided that such LLE has the syntactic role of the subject or any secondary member of the sentence, except for the definition (excluding definitions in the form common and participles) and other LLE of the second group of LLE, which are consistently subordinate to the LLE, the first of which is the LLE of the third HSS, which have a direct subordinate connection with the said chapter LLE of the second LLE group, up to the last LLE in the LLE chain with a continuous subordinate connection.

[116] The identification of elements 71 (first and second elements 71) of the sixth SM data structure during step 2032 is performed by identifying the main LLE of the first and second LLE groups, as well as identifying the other LLE of the first and second LLE groups. To identify the main LLE of the first LLE groups, it is necessary to reveal all the LLE “predicate” (including all parts of each LLE “predicate) of the analyzed sentence. To identify the main LLE of the second LLE groups, it is necessary to identify all LLEs that have a direct syntactic connection with any part of the LLE “predicate” and which at the same time have the syntactic role of the subject or any secondary member of the sentence, except for the definition (excluding the definition in the form of common participle or microparticle . To identify other LLE of the first or second LLE group, it is necessary to identify all LLE's that have a continuous syntactic subordinate relationship, starting from the main LLE of the first or second LLE group and up to another identified main LLE of the first or second LLE group, or the last LLE in a chain of continuous syntactic subordinate connection from the main LLE of the first or second group LLE. The formation of the first elements 71 of the sixth SMD data structure is carried out by combining the identified LLE of the first group of LLE and other LLE for this main LLE. The formation of the second elements 71 of the sixth SM data structure is carried out by combining the identified LLE main group of the second LLE group and other LLE for this main LLE.

[117] The identification of the value and ordinal (ordinal) number (s) of the TE of the first element 71 (first LLE group) of the sixth data structure of the MDD within step 2032 is as follows: the value (s) 211 of the TE 21 of the linguistic sentence 11 constituting the element (s) 61 of which (which) the first element 71 consists are identified as the value 711 of the first element 71 (the first LLE group), and the ordinal number (s) 212 of the said (mentioned) TE 21 linguistic sentence 11, constituting (constituting ) Element (s) 61, from which (whom) includes a first member 71, identified as sequence (sequence) number (s) 712 TE constituting (constituting) the first member 71 (the first group LLE). The identification of the value and ordinal (ordinal) numbers (numbers) of TEs of the second element 71 (second LLE group) of the sixth data structure of the SMD data as part of step 2032 is as follows: the value (values) 211 TEs 21 of the linguistic sentence 11 constituting ) 61, of which (which) the second element 71 consists, is identified as the value 711 of the second element 71 (second LLE group), and the ordinal number (s) 212 of the above (mentioned) TE 21 linguistic sentence 11 constituting (components) uh ement 61, from which (whom) includes a second member 71, identified as sequence (sequence) number (s) 712 TE constituting (components) of the second member 71 (the second group LLE).

[118] The formation of the sixth data structure of the MDD during step 2032 is performed by combining the first and second elements 71 of the sixth data structure of the DMD data and their identification data according to principles and methods known from the prior art in a single data structure, are described.

[119] Identification of linguistic characteristics of TEs that make up the first or second elements 71 (the first or second LLE group) of the sixth data structure of the MDD and their values, if necessary, is produced by organizing a query in the BDLP, formed as part of step 2031, consisting of the identification data of TEs the first or second element 71 (first or second LLE group), and obtaining the values (2131, 2141, 2231, 2151) of all parts of the linguistic characteristics (213, 214, 223, 215) of the text elements 21 of the linguistic sentence 11, of which the first left or second element 71 (the first or second group of LLE). At the same time, as described earlier, the linguistic features of the first and second elements 71 (first and second LLE groups) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, which the elements 71 (LLE groups) consist of.

[120] FIG. 23, by way of example, but not limitation, shows the general scheme for performing the steps of step 204 of forming the seventh data structure of the DMD, which is the third data structure for the method 200 in question. Step 204 is characterized by: performing step 2041 of identifying the types of elements 71 of the sixth data structure of the MDD the presence in element 71 of the complications of the linguistic sentence, which identify the first and second types of elements 71 of the sixth SMD data structure, as well as the identification of non-transformed elements 81 of the seventh structure the data paths of the SMD data and their identification data representing, for each non-transformed element 81, as an example, but not limitation, the value 811 of the non-transformed element 81 of the seventh SMD data structure and the ordinal number of the linguistic sentence 11 constituting ( components) non-transformed element 81 (value and sequence numbers of TE non-transformed element 81); performing step 2042 of generating the transformed elements 81 of the seventh SMD data structure, on which the transformed elements of the seventh MDD data structure are formed from the second type elements 71, as well as the identification data of the transformed elements 81, representing for each transformed element 81, as an example but not limitation , the value 811 of the transformed element 81 of the seventh data structure of the MDD and the ordinal (s) number (s) 812 TE of the linguistic sentence 11, constituting (components) razovanny element 81 (value and the converted ordinal numbers TE element 81); performing step 2043 of forming the seventh SMD data structure, wherein the seventh SMD data structure is formed from the transformed elements 81 and the non-transformed elements 81 of the seventh SMD data structure.

[121] FIG. 24 shows, by way of example, but not limitation, the general structure of the seventh SMD data structure that is the third data structure for this transformation method 200. The seventh SMD data structure is an SMD containing non-transformed elements 81 and transformed elements 81, which are basic linguistic-logical objects (OLLO) of the linguistic sentence 11. OLLO linguistic sentence 11 has characterizing their unique names (UN OLLO), which have practical and Use, as an example, but not limitation: "subject of judgment", "predicate judgments" and the like. In the data structure, elements 81 are referred to as unique names, and, by way of example, but not limitation, can be referred to as “UN OLLO n”, where n ≥ 1 is the ordinal index of the unique name element in the linguistic sentence, starting with “1” for each new UN OLLO, not previously encountered in the linguistic sentence. In the future, when OLLO is mentioned as an element of the seventh data structure, I mean the OLLO UN. The main linguistic-logical objects of a sentence are a border entity with signs of both linguistic and logical objects. An entity is an object in a computer system containing a set of critical rules. From the linguistic point of view, the main linguo-logical object is a syntactic unit of the form “syntactic structure”, which can be formed from the structured LLE group by heterogenizing the LLE group. Heterogenization of the LLE group is the elimination of homogeneity in the syntactic structure by identifying in it the syntactic, somatic link and converting the syntactic structure with homogeneities into several syntactic structures without homogeneities. A writing connection is a connection between syntactically equivalent sentence units (in this case between LLE), which have the same syntactically main word (main LLE) and the same syntactic role (syntactic role of LLE). LLE, between which syntactic and somatic connection is identified, are considered “homogeneous members” (LLE-POC). From a logical point of view, OLLOs are logical entities (objects) that are elements of a simple judgment, with the help of which they form and convey the idea that something (predicate of judgment) is affirmed or refuted about the subject of judgment (the subject of judgment). In this case, something (that which is affirmed or refuted about the subject of judgment) can be additionally logically structured. For example, but not limited to, a predicate of judgment can be divided into three logically separable logical entities (objects) —the action of the predicate of judgment, the object of the predicate of judgment, and the circumstances of the predicate of judgment. The elements of simple judgment mentioned above (subject of judgment, action of the predicate of judgment, object of the predicate of judgment, and circumstances of the predicate of judgment) mentioned above can be identified with separate UN OLLOs as separate syntactic constructions of the linguistic sentence 11. From the semantic point of view, OLLOs are generalized thinkable ( semantic image of the element of simple judgment.

[122] Identification of elements 71 of the first or second type of the sixth SMD data structure under step 2041 is performed by analyzing the values of the linguistic characteristics of the text elements of the sixth SMD data structure constituting element 71 (LLE group) in order to identify syntactic composing connections in the LLE group 71. The syntactic writing relationship between text elements (words, LLE) in the LLE 71 group is identified if such LLE (words) have the same syntactic parent (syntactic main word, which with such LLE (words) has a direct syntactic subordinate connection). Additional conditions may be that such LLE (words) have the same syntactic role, as well as the presence of an indication of a connection between such LLE (words), namely, a comma or a writing union. Writing unions are divided by value into connecting ("and", "yes" in the meaning of "and", "neither ... nor", "also", "also", "both ... and"), dividing (" either "," or ... or "," or "," either ... or "," then ... then "," whether ... whether "," not that ... not that " ) and adversary ("a", "but", "however", "yes" in the meaning of "but"), including comparative ("not only ... but", "" not only ... but and " , "Not only not ... but", "not so much ... how much"). Other own criteria for identifying a sociable link can be pre-set, or, for example, not limited to, ignoring any additional condition, for example, not limiting to the condition about the presence of a link sign, can be set. When identifying a syntactic intimate relationship in the LLE group, such LLE groups with homogeneous members are identified as the second type of element 71 of the sixth SMD data structure. All other LLE groups in which the syntactic composing link is not identified are identified as the first type of element 71 of the sixth data structure of the SMD. In this case, the identified first type element 71 of the sixth SMD data structure is identified with the non-transformed element 81 of the seventh SMD data structure. The formation of the transformed elements of the seventh SMD data structure (transformed elements 81, obtained from the second type elements 71) at step 2042 is performed based on the syntactic composing link identified at step 2041 and homogeneous members by transforming the identified second element elements 71 of the sixth data structure of the MDD. The meaning of the transformation of the element 71 of the second type at step 2042 consists in heterogenizing the LLE group, that is, eliminating syntactic homogeneities in the LLE group by forming from the element 71 of the second type a set of new LLE groups identical in homogeneity to the element 71 of the first type. Moreover, each new LLE group of the mentioned set can contain only one of the mentioned homogeneous members (if the element 71 of the second type contains one row of homogeneous members) or only one unique combination of the mentioned homogeneous members of different rows of homogeneous members (if the element 71 of the second type contains several rows of homogeneous members). The set of LLE groups formed from the element 71 of the second type are heterogeneous OLLO (transformed elements 81), that is, formed from one group of the LLE 71 of the second type by its heterogeneous transformation (heterogenization). The process of heterogenization of the elements 71 of the second type can be carried out, by way of example, but not limitation, as follows: in the first stage, rows of homogeneous members are detected in the analyzed element 71 of the second type; in the course of identifying the series of homogeneous members, the series of homogeneous members themselves and the sequence numbers of homogeneous members in the series, as well as signs of the connection of each homogeneous member (LLE-TOR), are identified; at the second stage, chains of homogeneous members are detected for each LLE-PCH element 71 of the second type; the chains of homogeneous members (chains of PTS) are LLE-POC and the dependent chain of PTS (a chain of syntactically related LLEs, starting from the first syntactic descendant of LLE-POC (a syntactically dependent word) and continuing along the chain of syntactic dependence (on a syntactic subordinate connection) another LLE-POC or to the last LLE in element 71 of the second type; the identified POC chains are classified according to the fact that there is a syntactic descendant of LLE in the dependent POC chain that is not included in the dependent POC chain; those POC chains that dependent PTS chains without a syntactic descendant outside the dependent POC chains are considered as extreme chains of homogeneous members (extreme chains of PTS), and those PEC chains that have dependent POC chains with a syntactic descendant beyond the framework of the dependent POC chains are considered as internal chains of homogeneous members (internal chains of PTS ); at the third stage, LLE of the element 71 of the second type, not included in the chains of homogeneous members (LLE outside the PTS chains), is detected; in the fourth stage, replaceable dependent chains (interchangeable SCs) of the element 71 of the second type are formed; at the same time, a replaceable SC is the basis of the transformed elements 81, consisting of one extreme PTS chain and internal PTS chains, if such internal PTS chains along a chain of continuous syntactic subordinate relationship exist between the PTS extreme chain and LLE outside the PTS chains; at the fifth stage, heterogeneous basic linguo-logical objects (OLLO) are formed; at the same time, a heterogeneous OLLO is formed from one interchangeable ZZ and LLE outside the PTS chain (if there are such LLE); the number of interchangeable replacement elements of the element 71 of the second type determines the number of heterogeneous OLLOs formed from one element 71 of the second type.

[123] The identification of the types of elements 71 of the sixth SMD data structure in step 2041 does not change the value 711 of element 71 and does not change the sequence numbers of the text elements 21 of the linguistic sentence 11 that make up element 71 (LLE group). Identification of the value and ordinal (ordinal) number (s) of TE non-transformed element 81 (OLLO) of the seventh SMD data structure in step 2041 is as follows: value (values) 211 TE 21 of linguistic sentence 11 constituting (making) element 71 of the first type sixth the data structures of the SMD are identified as the value 811 of the non-transformed element 81 (OLLO), and the serial number (s) 712 of the TE 21 of the linguistic sentence 11 constituting the constituent element 71 of which consists of This element 81 is identified as the ordinal (s) number (s) of 812 TEs constituting (components) the non-transformed element 81 (OLLO). The identification of the value and ordinal (ordinal) number (s) of the TE of the transformed element 81 (heterogeneous OLLO) of the seventh SMD data structure in the framework of step 2042 is performed as follows: the value (values) 211 of the TE 21 of the linguistic sentence 11 constituting the (component) element 71 of the second type the sixth data structure of the SMD, except for the value (values) 211 TE 21 of the linguistic sentence 11, constituting (constituting) a separate (separate) part (parts) of the element 71 of the second type (LLE-OCH), which (which) were (were) deleted ( distant) during heterogenization, and communication attributes of remote LLE-OCH (syntactically subordinate to remote LLE-OCH composes or punctuation marks) are identified as the value 811 of the transformed element 81 (OLLO), and the ordinal number (s) of 212 TE 21 of the linguistic sentence 11, constituting (constituting) element 71 of the second type of the sixth data structure of the SMD, except for the ordinal (s) number (s) 212 TE 21 of the linguistic sentence 11, constituting (constituting) separate (separate) part (s) of the elements those 71 of the second type (LLE-OCH), which (which) were (were) removed (removed) during heterogenization, and the communication signs of the deleted LLE-OCH (syntactically subordinate to the remote LLE-OCH, composing associations or punctuation marks) are identified as ordinal (ordinal ) number (s) 812 TE, constituting (making) the transformed element 81 (heterogeneous OLLO).

[124] The formation of the seventh MDD data structure in step 2043 is performed by combining the elements of the seventh seventh SMD data structure, as well as their identification data according to principles and methods known from the prior art, in one data structure identified at step 2041 and formed at step 2042. , accordingly, further are not described in detail. The first of the merged elements of the seventh SMD data structure is the element identified at step 2041 as the element 71 of the first type, which is the untransformed element 81, that is, OLLO 81, which coincides with the LLE group 71 without syntactic composing. The second of the combined elements of the seventh SMD data structure is the transformed elements 81, formed at step 2042 as a set of transformed elements 81 that are heterogeneous OLLOs, formed from the element 71 of the second type (LLE groups with syntactic composer link) by heterogenizing the LLE groups of the second type.

[125] Identification of linguistic characteristics of TEs that make up the first or second elements 81 (OLLO) of the seventh MDD data structure and their values, if necessary, is produced by organizing a query in the BDLP, formed as part of step 2031, consisting of the identification data of TEs that make up the first or second element 81 (OLLO), and obtaining the values (2131, 2141, 2231, 2151) of all parts of the linguistic characteristics (213, 214, 223, 215) of the text elements 21 of the linguistic sentence 11, of which the first or second element 81 (OLLO) consists. At the same time, as described earlier, the linguistic features of the elements 81 (OLLO) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which the elements 81 (OLLO) consist.

[126] Further, after completing the previously described step 204, in order to further improve the accuracy of subsequent search in a structured dataset (SMD), it becomes possible to further convert the SMD containing at least the basic linguistic objects offers and their identification data.

[127] FIG. 25, by way of example, but not limitation, depicts a general scheme for performing the steps of the claimed method 300 for converting an SMD containing at least the main linguistic-logical objects (OLLO) of the linguistic sentence and the identification data of the OLLO, which is the initial data structure for the method 300 in question The claimed method 300 for converting an SMD containing at least the OLLO linguistic sentence and the OLLO identification data is characterized by: performing an identification step 301 suitable for Formation of a data structure containing an OLLO, which identifies an MCD data structure containing the elements of a convertible data structure containing an OLLO, which is the initial structure of the MCD data in the framework of the considered method 300, and logical objects (OLLO) linguistic sentences and identification data OLLO; performing step 302 of forming the eighth MDD data structure, which forms the eighth MDD data structure, which is the first MDD data structure for the considered method 300, containing the elements of the eighth SMD data structure, and the said elements of the eighth MDD data structure are the original simple linguistic-logical structures (IP LLK) linguistic sentences, formed from syntactically related OLLO simple sentences of the original linguistic sentence, as well as are a SP data identification LLK representing for each SP LLK, as an example, but not limitation: SP value LLK and sequence numbers TE linguistic proposals constituting SP LLK; the execution of step 303 of forming the ninth MDD data structure, which forms the ninth MDD data structure, which is the second MDD data structure for the considered method 300, containing elements of the ninth SMD data structure, and these elements of the ninth MDD data structure are simple linguistic-logical structures (PLC a) linguistic sentences, formed from the PI LLK by eliminating the homogeneities in the PI LLK, and also represent the identification data of the PLC, which represent zhdoy PLLK, as an example, but not limited to: the value and serial numbers PLLK TE linguistic supply components PLLK; the step 304 of forming the tenth data structure of the DMD, which forms the tenth data structure of the DMD, which is the third data structure of the MDD data for the method 300, containing the element of the tenth data structure of the MDD, and the element of the tenth data structure of the MDD is the initial complex linguistic-logical structure (IS LLK) linguistic sentence, formed by combining all PLC with the syntax of PLC in the original linguistic sentence, as well as edstavlyaet an identification data IC LLC, representing, as an example, but not limited to: the value of IP and serial numbers LLC TE linguistic proposals constitute LLC IC; the execution of step 305 of forming the eleventh data structure of the MDD, which forms the eleventh data structure of the DMD, which is the final data structure of the MDD data for the method 300, containing elements of said eleventh data structure of the DMD, and these elements of the eleventh data structure of the MDD are complex linguistic-logical structures ( SLC) of the linguistic sentence, formed from the IS LLK by eliminating the homogeneities in the IS LLK, and also represent the identification data SLLCs, representing for each SLLC, as an example, but not a limitation: the SLLC value and the sequence numbers of the TE language of the linguistic sentence that make up the SLCK.

[128] FIG. 26, by way of example, but not limitation, depicts a general scheme for the implementation of identification stage 301 for converting a data structure containing basic linguistic entities (OLLO), which is the initial data structure for method 300 under consideration. Step 301 is characterized by performing identification suitable for conversion a data structure containing an OLLO, on which elements 91 of a data structure suitable for conversion, containing an OLLO, are identified, as well as the identification data of the elements 91, amounts to the OLLO for each, as an example, but not limitation, a value element 911 91 is suitable for converting the data structure comprising OLLO and sequence (sequence) number (s) 912 Offer linguistic TE 11 constituting the (constituent) element 91.

[129] FIG. 27, as an example, but not limiting, a general data structure is shown that is the source for the present transformation method 300, which is a convertible data structure containing the main linguistic-logical objects (OLLO). The original data structure is an SMD containing elements 91 of a data structure suitable for conversion, containing OLLOs, which are the main linguistic-logical objects (OLLOs) and the OLLO identification data representing, for each OLLO, as an example, but not limitation, the value 911 an element 91 of a data structure that is suitable for conversion and contains the ordinal (s) number (s) 912 of the TE of the linguistic sentence that make up the sLL, which, as an example, but not og The limitations have been described previously with reference to FIG. 24 ways 200. The element 91 of the linguistic sentence 11 has characterizing their unique names (UN OLLO), which have practical use as an example, but not limitation: “subject of judgment”, “action of the predicate of judgment” and the like. In the data structure, elements 91 are referred to as unique names, by way of example, but not limitation, may be referred to as “UN OLLO n”, where n ≥ 1 is the ordinal index of the unique name element in the linguistic sentence, starting with “1” for each new UN OLLO not previously encountered in the linguistic sentence. As mentioned earlier, from the linguistic point of view, OLLOs represent a syntactic unit of the form “syntactic construction”, which can be formed from LLE structured groups; from a logical point of view, OLLOs are elements of a simple judgment, with the help of which something is affirmed or refuted about the subject of judgment; From the semantic point of view, OLLOs represent a generalized conceivable (semantic) image of the element of simple judgment. The elements 91 of a convertible data structure containing OLLO are a set of unique names (UNOLLO) of the linguistic sentence 11. a data structure containing an OLLO in the form of a structured array (list, list, and the like) of individual OLLOs. Such preparatory actions may be carried out by any method known from the prior art or by a method unknown from the prior art, such as the method specified in the description of method 200, and, accordingly, are not described further below.

[130] The identification of the elements 91 of the data structure that is suitable for conversion that contains OLLO, during step 301, is reduced to the classification of the elements that make up the transformation of the data structure that contains the OLLOs as the main linguistic objects (OLLO 91). Moreover, all OLLO 91 have the values 911 and the ordinal numbers of the textual elements 912 of the linguistic sentence that constitute OLLO. The 911 OLLO 91 values represent one or more text elements (TE 21) of Proposition 11, of which OLLO is composed. The number of FCs that make up OLLO is related to the technical ability of a language when describing an object, an action or its signs, or the need of the author to describe the entities of the surrounding world (objects, actions or their signs) to use a certain linguistic description method, as an example, but not limitation , we can give the following various ways of linguistic description of the same entity: “old man” = “old man” = “old man” and the like. This entity can be linguistically expressed through one, two or three TE. At the same time, for example, without being limited to, the essence of “consumer rights” cannot be linguistically expressed in Russian as one TE.

[131] The identification of the 911 value of the element 91 (OLLO) of the data structure containing the OLLO that is suitable for conversion during step 301 is performed by registering a set of characters of the text elements 21 of the sentence 11, of which the OLLO 91 consists. Identification of the ordinal number (s) 912 TE, of which (which) element 91 (OLLO) of the data structure containing OLLO, which is suitable for conversion, is composed, during step 301, is produced by registering ordinal (s) numbers (s) of said TE in accordance with their location in lin in a linguistic sentence, provided that the first TE in the linguistic sentence has the number “1”, and all subsequent TEs have a sequence number greater by one than the sequence number of the previous TE.

[132] The conversion-suitable data structure containing the OLLO, which is the source for the present transformation method 300, is ultimately a plurality of elements 91, their values 911 and sequence numbers 912 TEs constituting the elements 22 identified in step 301.

[133] Identification of linguistic characteristics of TE, constituting elements 91 (OLLO) of a data structure containing OLLO, which is suitable for conversion, and their values, if necessary, is produced by organizing a query into BDLP, formed under step 2031, consisting of identification data of TE, constituting element 91 (OLLO), and obtaining the values (2131, 2141, 2231, 2151) of all parts of the linguistic characteristics (213, 214, 223, 215) of the text elements 21 of the linguistic sentence 11, of which the element 91 (OLLO) consists. At the same time, as described earlier, the linguistic features of elements 91 (OLLO) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which the elements 91 (OLLO) consist.

[134] FIG. 28, by way of example, but not limitation, a general scheme of performing the steps of step 302 of forming the eighth SMD data structure, which is the first data structure for the method 300 under consideration, is shown. constituting elements 91 of a data structure suitable for transformation, containing the OLLO on which the values 2161 of the fifth part of the linguistic characteristics 216 of the elements 21 constituting the elements 91 are formed and ie the information obtained in BDLP text elements 21 linguistic Proposition 11 that is generated in phase in 2031, eventually forming BDLP text elements 21 linguistic Proposition 11, formed in 3021 under the stage; performing step 3022 of forming the elements of the eighth SMD data structure on which the elements 12 of the eighth SMD data structure are formed, as well as the identification data of the elements 12 representing for each element 12, as an example, but not limitation, the value 121 of the element 12 of the eighth SMD data structure and sequence numbers 122 TE linguistic sentences 11, constituting the elements 12, and form the eighth structure of the data SMD.

[135] FIG. 29, by way of example, but not limitation, shows the general structure of the linguistic characteristics database (BDLP) formed during step 3021, which is the BDLP text elements 21 of sentence 11 contained in elements 91 suitable for transforming a data structure containing an OLLO. The BDLP, formed in step 3021, differs from the BDLP, formed in step 2031, by the presence of 2161 fifths of the linguistic characteristics 216, indicating the syntactic role of element 91 (OLLO). Since from the linguistic point of view OLLO is a syntactic construction, it is natural that in one sentence some syntactic constructions relative to other syntactic constructions, if there is a syntactic subordinate connection between them, are syntactically main or syntactically dependent. According to this principle, some OLLOs can be syntactically main (main OLLOs), and others - syntactically dependent (dependent OLLOs). The identification of the fifth part of the linguistic characteristics of 216 textual elements 21 of the linguistic sentence 11, which constitute OLLO 91 and their meanings 2161, is reduced to the classification of OLLO 91 by their syntactic role. The syntactic role of OLLO is identified with the syntactic role of the main LLE in OLLO 91. Using the value 2161 of the fifth part of the linguistic characteristics 216 elements 21 constituting OLLO 91, all OLLO 91 is divided into main OLLO 91 and dependent OLLO 91.

[136] The formation of the fifth part of the linguistic characteristics 216 and their meanings 2161 during step 3021 is performed by analyzing the existing linguistic characteristics of element 91. During such analysis, for example, but not limitation, the following actions can be performed: syntactically main LLE; at the second stage, among the linguistic features of the main LLE mentioned OLLO 91 identify the linguistic characteristic responsible for the syntactic role of the syntactically main LLE of element 91; at the third stage, the value of the identified linguistic characteristic responsible for the syntactic role of the syntactically main LLE is checked; if the value (the syntactic role of the syntactically main LLE of element 91) is “predicate”, then such OLLO 91 (syntactically the main LLE of element 91) gets the value 2161 of the fifth part of linguistic characteristics 216 - “main OLLO”; if the value is not “predicate”, then such OLLO 91 (syntactically main LLE of element 91) gets the value 2161 of the fifth part of linguistic characteristics 216 - “dependent OLLO”. As a result, 2161 fifths of the linguistic characteristics 216 are formed for all elements 91 (OLLO).

[137] Formed at the end of step 3021, the values 2161 (the syntactic role of the syntactically main LLE element 91) of the fifth part of the linguistic characteristics 216 of elements 21 constituting OLLO 91, suitable for transforming the data structure containing OLLO, are inserted into the BDLP of text elements 21 of the linguistic sentence 11, formed as part of stage 2031, forming as a result the BDLP of textual elements 21 of the linguistic sentence 11, formed within the framework of stage 3021. All parts (211, 214, 232, 215 and 216) of the linguistic characteristics of textual elements 21 linguistic sentences 11 and their meanings (2111, 2141, 2321, 2151 and 2161) form the unique linguistic attributes of the elements 91.

[138] FIG. 30, by way of example, but not limitation, depicts the general structure of the eighth formed data structure of the DMD, which is the first data structure of the MDD data for this conversion method 300. The eighth data structure of the MDD is the MDD containing elements 12 of the eighth data structure of the DMD, which are the original simple linguistic-logical constructions (PI LLK 12) of the linguistic sentence 11 and identification data of the IP LLK, representing for each IP LLK, as an example, but not limitation, the value of 121 e Item 12 of the eighth data structure and sequence numbers of text elements 122 that make up the IP LLK (value and sequence numbers of TE element 12). The IP LLK 12 of the linguistic sentence 11 lacks the unique names that characterize them, which have practical use. In the data structure, elements 12, as an example, but not limitation, may be referred to as “IP LLK-1”, “IP LLK-2”, “IP LLK-3”, “IP LLK-n”, where n ≥ 1 - The ordinal number of the element in the linguistic sentence. IP LLK sentences - is the border entity between linguistics and logic. From a linguistic point of view, the IP LLK is a syntactic unit of the “syntactic structure” type, formed from OLLO by combining OLLO on the basis of the presence of a direct syntactic subordinate or composing link between OLLO. The mentioned direct syntactic subordinate or writing link means the presence between the elements of different OLLO (between LLE different OLLO) syntactic subordinate or writing link. From the point of view of the syntax, the IP LLK is a separate source simple sentence or a source simple sentence as part of the original compound sentence. In this case, the initial simple sentence in the IP LLK may contain homogeneous members, that is, words, between which there is a syntactic somatic connection. From a logical point of view, PI LLK is a logical entity that expresses a simple judgment (non-quantifier judgment), which is a primary logical construction of thinking, through which the thought is formed and transmitted that something (the predicate of judgment) is affirmed or refuted about the subject of judgment (subject judgments). In this case, something (that which is affirmed or refuted about the subject of judgment) can be additionally logically structured. For example, without limitation, the predicate of judgment can be divided into three logically separable entities — the action of the predicate of judgment, the object of the predicate of judgment, and the circumstances of the predicate of judgment. The elements of simple judgment mentioned for example can be identified with separate UN OLLO (OLLO of the unique name), from which IP LLK is formed. Quantifying simple judgment is determined by its “quantitative characteristic”, that is, by the presence or absence of uniqueness in a simple judgment. According to the quantitative characteristic (quantification), all simple judgments can be divided into two categories: single-valued simple judgments and ambiguous simple judgments. Unambiguous simple judgments are simple quantifier judgments, in which the quantifier index is always defined and equal to one, that is, each element of a simple judgment has no variability, is always single-valued. The uniqueness of a simple judgment is manifested by finding in a simple judgment elements of a simple judgment of a single unique name (NR) in a single quantity (for example, without limitation, one subject of the judgment, the object of the predicate judgment, the action of the predicate judgment or one homogeneous circumstance of the predicate judgment). An example of a straightforward simple judgment is the following judgment: “The goods must be transferred to the buyer by the seller.” This simple judgment does not allow any ambiguity - only the “goods”, only “must be transferred”, only the “buyer” and only the “seller”. Ambiguous simple judgments are simple quantifier judgments in which at least one element of a simple proposition of a unique name (UI) quantifierity is always defined and always greater than one, that is, an element of simple judgment is always ambiguous in an ambiguous simple proposition. The ambiguity of a simple judgment is manifested by finding in the composition of a simple judgment several elements of a simple judgment of one unique name (NP) (for example, without limitation, several subjects of judgment and (or) objects of a predicate of judgment and (or) actions of a predicate of judgment and (or) several homogeneous circumstances predicate judgments). An example of an ambiguous simple judgment is the following judgment: “The goods must be transferred to the buyer by the seller or manager of the company”. This simple judgment allows ambiguity due to the presence in it of two elements of a simple judgment with the same DCs - the subjects of the seller and the manager of the company, each of which can be applied to the predicate judgment “must transfer the goods to the buyer”. If simple judgments that are in a certain array of simple judgments (a separate, separate group of simple judgments) have the same quantitative characteristic (quantifier index is one or more than one), then regardless of the quantifier type of simple judgment (single-valued or ambiguous) simple judgments of such an array are “quantifier”. If simple judgments that are in a certain array of simple judgments (a separate, separate group of simple judgments) do not have the same quantitative characteristic (the quantifier index of simple judgments can be either equal to one or greater than one), then simple judgments Arrays are referred to as “non-quantifiers” (without a certain quantifier). In connection with the foregoing, IP LLK, formed from the OLLO of the original sentence, between which there is a syntactic and somatic connection, can be classified only as a “non-quantifier” simple judgment, since nothing guarantees the presence of the same quantitative characteristic of all simple judgments directly (without any additional processing) generated from an arbitrary source linguistic sentence.

[139] The formation of elements 12 of the eighth data structure of the DMD, which are the original simple linguistic-logical constructions (PI LLK) during step 3022, is based on the results of identifying the 2161 values of the fifth part of the linguistic characteristics 216 of the elements 21 constituting OLLO 91. To form the element 12 the eighth data structure of the MDD is necessary to perform the following steps: in the first stage, choose the main OLLO 91; at the second stage, all dependent OLLO 91s subordinate to him are identified using the values 2161 of the fifth part of the linguistic characteristics 216 of the elements 21 constituting OLLO 91; at the third stage, among the identified dependent OLLO 91, such OLLO 91 is identified, which have a direct subordinate relationship with the previously selected OLLO 91; at the fourth stage, a preliminary element 12 of the eighth SMD data structure is formed, which is the initial simple linguistic-logical structure (IP LLK), by combining the selected “main OLLO 91” and all identified “dependent OLLO 91” having direct subordinate links with the selected main OLLO 91 ; at the fifth stage, the identified OLLOs are identified among the already identified dependent OLLOs 91 using the values 2131 of the first part of the linguistic characteristics 213 of the elements 21 constituting the OLLO 91. To complete the formation of the element 12 form a query in the BDLP formed within the framework of step 3021 to check for signs of a connection between the combined OLLO, and, in the presence of such signs, receive a text element (text elements), identified (identified) as one of (or several of, or a combination of): punctuation, union or union word, located between the merged ollo.

[140] The identification of the meaning and sequence numbers of the TE element 12 of the eighth SMD data structure is performed in step 3022 by identifying the value 121 of element 12 with the values 911 of the elements 91 to be merged and the values 211 of text elements, which are attributes of the connection according combinable elements 91, and the ordinal numbers 122 of text elements 21 constituting element 12 with the ordinal numbers 912 of text elements constituting the elements 91 to be merged and order Vym numbered textual elements 21, which are signs of connection between the identified elements 91 combinable.

[141] The formation of the eighth MDD data structure during step 3022 is carried out by combining the eighth eighth SMD data structure and their identification data according to principles and methods known from the prior art, which, respectively, are not described in further detail in one data structure.

[142] Identification of linguistic characteristics of TE, constituting elements 12 (IP LLK) of the eighth SMD data structure, and their values, if necessary, is produced by organizing a query in BDLP, formed under step 3021, consisting of identification data of TE, constituting element 12 ), and obtaining the values (2131, 2141, 2231, 2151, 2161) of all parts of the linguistic characteristics (213, 214, 223, 215, 216) of the text elements 21 of the linguistic sentence 11, of which element 12 consists (PI LLK). At the same time, as described earlier, the linguistic features of elements 12 (PI LLK) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, which constitute elements 12 (IP LLK).

[143] FIG. 31, by way of example, but not limitation, a general scheme for performing the steps of step 303 of forming the ninth SMD data structure, which is the second data structure for the considered method 300, is shown. Step 303 is characterized by: performing step 3031 of identifying the types of elements 12 of the eighth MDD data structure indicating the presence in IP LLK of composed OLLOs, which identify the first and second types of elements 12 of the eighth SMD data structure, and also identify the non-transformed elements 13 of the ninth SMD data structure and their identifiers The icing data representing, for each non-transformed element 13, as an example, but not limitation, the value 131 non-transformed element 13 of the ninth SMD data structure and the serial numbers 132 of the TE language of the linguistic sentence 11 constituting element 13 (the value and numbers of the TEs of the non-transformed element 13) ; performing step 3032 of generating the transformed elements 13 of the ninth SMD data structure, on which the transformed elements 13 of the ninth SMD data structure of the second type of elements 12 are formed, and also the identification data of the transformed elements 13, representing for each transformed element 13, as an example, but not restrictions, the value 131 of the transformed element 13 of the ninth data structure of the MDD and the serial 132 numbers of the TE of the linguistic sentence 11 constituting the element 13 (the value and the sequence number TE transformed member 13); performing step 3033 of forming the ninth SMD data structure, wherein the ninth SMD data structure is formed from the transformed elements 13 and the non-transformed elements 13 of the ninth SMD data structure.

[144] FIG. 32, by way of example, but not limitation, depicts the general structure of the ninth SMD data structure formed, which is the second SMD data structure for this conversion method 300. The ninth SMD data structure is a SMD containing elements 13, which are simple linguistic-logical structures (PLC) of the linguistic sentence 11, and the PLC identification data representing for each PLC, as an example, but not limited to, the value 131 of the 13th of the ninth data structure and order stems rooms 132 text elements constituting PLLK. Elements 13 of the ninth data structure of the SMD are subdivided according to the principle of their formation into non-transformed elements 13 and transformed elements 13. PLC 13 linguistic sentence 11 does not have any unique names that characterize them, which have practical use. In the data structure, elements 13, by way of example, but not limitation, may be referred to as “PLC1”, “PLC2”, “PLCC3”, “PLCCn”, where n ≥ 1 is the sequence number of the element in the linguistic sentence. The linguistic sentence 11 PLC is the borderline between linguistics and logic. From a linguistic point of view, a PLC is a syntactic unit of the “syntactic construction” type, formed from an IP LLK by heterogenization of an IP LLK. From the point of view of syntax, PLC is a separate simple sentence or a simple sentence as part of the original complex sentence, which does not contain homogeneous members (words between which there is a syntactic compositional link). From a logical point of view, PLC is a logical entity expressing a simple judgment (quantifier judgment), which is a primary logical construction of thinking, through which the thought is formed and transmitted that something (judgment predicate) is affirmed or refuted about the subject matter of judgment (subject of judgment ). In this case, something (that which is affirmed or refuted about the subject of judgment) can be additionally logically structured. For example, without limitation, the predicate of judgment can be divided into three logically separable entities — the action of the predicate of judgment, the object of the predicate of judgment, and the circumstances of the predicate of judgment. The elements of simple judgment mentioned for example may be identified with particular types of OLLOs from which the PLC is formed. The difference between PLC and IP LLK in the quantifier of simple judgment. If the PI LLC admits the possibility of the presence of ambiguity in a simple judgment, then the PLC has a quantifier index of one, which completely identifies the PLC with an absolutely single-valued simple judgment. In the composition of the PLC, there cannot be several elements of a simple judgment of one unique name (NR). For example, without being limited to, a PLC cannot include several subjects of judgment, and (or) objects of the predicate of judgment, and (or) actions of the predicate of judgment, and (or) homogeneous circumstances of the predicate of judgment. In PLC, there can be no ambiguity either in the subject of the judgment, or in the predicate of the judgment, regardless of the composition and design of the original linguistic sentence.

[145] Identification of the types of elements 12 of the eighth SMD data structure in step 3031 is performed by analyzing the values of the linguistic characteristics of text elements 12 (IP LLK) in order to identify syntactic composing links in the IP LLK 12. Syntactic composing connection between the OLLO (element 91) in the PI LLK 12 identify if the syntactically main LLE of such OLLOs have the same syntactic parent (the syntactically main word that has a direct syntactic subordinate connection with such LLE). Additional conditions may be that the main LLE of such OLLOs have the same syntactic role, as well as the presence of a sign of a connection between such LLE, namely, a comma or a writing union. When identifying a syntactic, somatic connection between the main LLE of two or more OLLOs, such IP LLKs are identified as the second type of element 12 (IP LLK) of the eighth SMD data structure. All other elements 12 (IP LLK) in which the syntactic composing relationship of the main LLE is not identified is identified as the first type of element 12 (IP LLK) of the eighth SMD data structure. In this case, the identified first type of element 12 of the eighth SMD data structure is identified with the non-transformed element 13 of the ninth SMD data structure. The formation of the transformed elements of the ninth data structure of the DMD (transformed elements 13 obtained from elements 12 of the second type) at step 3032 is made on the basis of the syntactic composing relationship identified between elements 91 (OLLO) element 12 (IP LLK) identified at step 3031 by converting element 12 of the second type . The meaning of the transformation of the element 12 of the second type at step 3032 is to heterogenize the PI LLK 12, that is, to eliminate syntactic homogeneities in the PI LLK 12 by forming from the second element 12 a set of new PLCs that are identical in homogeneity to the element 12 of the first type. Moreover, each new PLC of the mentioned set can contain only one of the mentioned OLLO 91 with homogeneous members (if element 12 of the second type contains one row of homogeneous members) or only one unique combination of the mentioned OLLO 91 with homogeneous members of different rows of homogeneous members (if element 12 of the second species contains several rows OLLO 91 with homogeneous members). Many PLLK (elements 13), formed from the element 12 of the second type are heterogeneous PLC, that is, formed from a single PI LLK 12 of the second type through its heterogeneous transformation (heterogenization). The process of heterogenization of IP LLK 12 of the second type can be carried out, as an example, but not limitation, as follows: at the first stage, rows of homogeneous members in the element 12 of the second type are detected; in the course of identifying the series of homogeneous members, they themselves identify the series of homogeneous members and the sequence numbers of homogeneous members in the series, as well as signs of the connection of each homogeneous member; at the second stage, chains of homogeneous members are detected for each identified OLLO containing the LLE-OCH (OLLO-OCH) element 12 of the second type; chain of homogeneous members (chain of PTS) is the OLLO-POC and dependent chain of homogeneous members (a chain of syntactically related OLLOs, starting from the first syntactic descendant of homogeneous members (syntactically dependent OLLO) and continuing along the chain of syntactic dependence (on the syntactic subordinate connection) to another OLLO -OCH or until the last OLLO in the element 12 of the second type; the identified POC chains are classified by the fact that there is a syntax descendant of LLE in the dependent PTS chain that is not included in the dependent POC chain; PTS chains that have dependent PTS chains without a syntactic descendant beyond the dependent chain of homogeneous members are considered extreme chains of homogeneous members (extreme CSCs), and those PZh chains that have dependent POC chains with a syntactic descendant beyond the dependent chains of PTS are considered internal chains of homogeneous members (internal chains of OFC); in the third stage, OLLO of element 12 of the second type is detected that are not included into chains of OFC (OLLO outside of chains of OFC); in the fourth stage, replaceable dependent chains (interchangeable replacement centers) of the element 12 of the second type are formed; removable SC is the basis of the transformed elements 13, consisting of one extreme chain of PSh and internal chains of PS, if such internal chains of PS are along the chain of a continuous syntactic subordinate connection between the extreme chain of PS and the OLLO outside the chains of PS. at the fifth stage, heterogeneous PLCs are formed (transformed elements 13); Heterogeneous PLLK is formed from one interchangeable LC and OLLO outside the PTS chain (if there are such OLLOs); the number of interchangeable replacement elements of the second type element 12 determines the number of heterogeneous PLCs (transformed elements 13) formed from one element 12 of the second type.

[146] The identification of the types of elements 12 of the eighth MDD data structure under step 3031 does not change the value 121 of element 12 and does not change the sequence numbers of the text elements 21 of the linguistic sentence 11 constituting element 12 (IP LLK). The identification of the value and sequence numbers of the TE of the non-transformed element 13 (PLC) of the ninth SMD data structure in step 3031 is as follows: the values 211 of the text elements 21 of the linguistic sentence 11 constituting the element 12 of the first type of the eighth data structure of the MDD are identified as 131 131 PLC), and the sequence numbers 212 of the above-mentioned text elements 21 of the linguistic sentence 11, constituting the element 12 of which the non-transformed element 13 consists, are identified as oryadkovye number 132 text elements constituting the unconverted element 13 (PLLK). The value and sequence numbers of the TE converted element 13 (heterogeneous PLC) of the ninth SMD data structure in step 3032 are identified as follows: 211 text elements 21 of the linguistic sentence 11 constituting element 12 of the second type of the eighth SMD data structure, except for 211 text elements 21 of the linguistic sentence 11, which make up separate parts of the element 12 of the second type (OLLO-OCH), which were removed during heterogenization, and signs of the connection between the remote OLLO-OCH (syntactically the subordinate main LLE remote allorders or punctuation marks) are identified as the value 131 of the transformed element 13 (PLC), and the ordinal numbers 212 of the text elements 21 of the linguistic sentence 11 constituting the element 12 of the second type of the eighth SMD data structure, except for the ordinal numbers 212 text elements 21 of the linguistic sentence 11, which constitute separate parts of the second type element 12 (OLLO-OCH), which were removed during heterogenization, and the connection signs of the deleted OLLO-OCH (syntactically subordinates to the main LLE by remote OLLO-OCH composing unions or punctuation marks) are identified as the ordinal numbers 132 of the text elements constituting the transformed element 13 (heterogeneous PLC).

[147] The formation of the ninth MDD data structure in step 3033 is performed by combining the elements of the ninth ninth SMD data structure previously identified in steps 3031 and 3032 and their identification data according to principles and methods known from the prior art, which are not described in further detail below. The first of the merged elements of the ninth data structure of the MDD is the element 12 of the first type identified at step 3031, which is the untransformed element 13, that is, PLC 13, which coincides with the PI LLK 12 without a syntactic composing relationship. The second of the merged elements of the ninth data structure of the DMD are the transformed elements 13, formed at step 3032 as a set of transformed elements 13, which are heterogeneous PLLK 13, formed from the element 12 of the second type (PI LLK with syntactic composing link) by heterogenizing IP LLK of the second type.

[148] Identification of linguistic characteristics of FCs that make up the non-transformed or transformed elements 13 (PLC) of the ninth data structure of the MD, and if necessary, their values are produced by organizing a query into the BDLP, formed during step 3021, consisting of the identification data of the TEs that compose the non-transformed or transformed element 13, and obtaining the values (2131, 2141, 2231, 2151, 2161) of all parts of the linguistic characteristics (213, 214, 223, 215, 216) of the textual elements 21 of the linguistic sentence 11, which consist of transformed or transformed element 13 (PLC or heterogeneous PLC). At the same time, as described earlier, the linguistic features of non-transformed and transformed elements 13 (PLC or heterogeneous PLC) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which elements 13 consist (PLC and heterogeneous PLC).

[149] FIG. 33, by way of example, but not limitation, shows a general scheme for performing the steps of step 304 of forming the tenth data structure of the DMD which is the third data structure for the method 300 in question. Step 304 is characterized by: performing step 3041 of generating values 2171 of the sixth part of the linguistic characteristics 217 of the elements 21 elements 13 of the ninth MDD data structure, on which the 2171 values of the sixth part of the linguistic characteristics of 217 elements 21 constituting elements 13 are formed, and the obtained information is entered into the BDLP t Kstovo linguistic elements 21 Proposition 11, formed in 3021 under the stage, forming eventually BDLP text elements 21 linguistic Proposition 11, formed in 3041 under the stage; performing step 3042 of identifying the types of elements 13 of the ninth SMD data structure indicating the presence of written PLCs, which identify the first and subsequent types of elements 13 of the ninth data structure of the MDS; performing step 3043 of identifying elements 14 as constituent parts of element 15 of the tenth SMD data structure, which identifies elements 14 of the tenth data structure of the DMD, as well as the identification data of elements 14 representing 141 for each element 14, as an example, but not limited to the element 14 of the tenth data structure of the MD and the sequence numbers 142 TE linguistic sentences 11, constituting the element 14; and form the tenth structure of the data of the MDD by combining elements 14 as components of a single element 15 of the tenth data structure of the DMD.

[150] FIG. 34, by way of example, but not limitation, shows the general structure of the linguistic characteristics database (BDLP) formed during step 3041, which is the BDLP text elements 21 of sentence 11 contained in elements 13 of the ninth MDD data structure. The BDLP formed in step 3041 differs from the BDLP formed in step 3021 by the presence of the sixth part of linguistic characteristics 217 and their meanings 2171 text elements 21 contained in elements 13, which establishes the syntactic role of PLC (elements 13 of the ninth MDD data structure). The syntactic role of a PLC can have values: the main PLC or the dependent PLC. Since from the linguistic point of view PLC is a syntactic construction, it is natural that in one sentence some syntactic constructions relative to other syntactic constructions, if there is a syntactic subordinate connection between them, are syntactically main or syntactically dependent. According to this principle, some PLCs can be syntactically main (main PLCs), while others - syntactically dependent (dependent PLCs).

[151] The formation of the sixth part of the linguistic characteristics 217 and their meanings 2171 for the textual elements 21 of the linguistic sentence 11 constituting the PLC 13 is made by classifying the PLC 13 by their syntactic role during step 3041. The syntactic role of the PLC is identified with the syntactic role of the main LLE in the main OLLO 91 in PLC 13. In accordance with the value 2171 of the sixth part of the linguistic characteristics 217 elements 21 constituting PLC 13, divide all PLC 13 into main PLC 13 and dependent PLC 13. Forming the sixth part of the ling 217 and their values 2171 are produced by analyzing the existing linguistic features of the elements 21 that constitute PLC 13. During such analysis, as an example, but not limitation, the following actions can be taken: at the first stage, syntactically main LLE is identified in all PLC 13 the main OLLO 91; in the second stage, among the linguistic features of the mentioned main LLEs of the mentioned PLC 13, a linguistic characteristic is identified that is responsible for the syntactic role of the mentioned syntactically main LLE of element 13; at the third stage, the value of the identified linguistic characteristic responsible for the syntactic role of the syntactically main LLE is checked; if the meaning (the syntactic role of the mentioned syntactically main LLE of element 13) is “predicate”, then such a PLC 13 (syntactically main LLE of the syntactic main element 91) provide the value 2171 of the sixth part of the linguistic characteristics 217– “main PLC”; if the meaning is not “predicate”, then such PLC 13 provides the value 2171 of the sixth part of the linguistic characteristics 217 - “dependent PLC”. In the end, form the values of 2171 of the sixth part of the linguistic characteristics 217 for all elements of PLC 13.

[152] Formed according to the results of step 3041, the values of 2171 (the syntactic role of the syntactically main LLE of the syntactically main OLLO element 13) of the sixth part of the linguistic characteristics 217 of elements 21 constituting the PLC 13 of the ninth data structure of the MDD are added to the BDLP of text elements 21 of the linguistic sentence 11 formed within of step 3041. All the parts (211, 214, 232, 215, 216 and 217) of the linguistic characteristics of the textual elements 21 of the linguistic sentence 11 included in the PLLC 13 and their meanings (2111, 2141, 2321, 2151, 2161 and 2171) form unique l ngvisticheskie features 13 elements.

[153] FIG. 35, by way of example, but not limitation, depicts the general structure of the formed tenth SMD data structure, which is the third SMD data structure for the present conversion method 300. The tenth MDD data structure is the SMD containing element 15, which is the original complex linguistic-logical the construction (IPLQ) of the linguistic sentence 11, and the identification data of element 15, representing, by way of example, but not limitation, the value 151 of element 15 of the tenth data structure and order marketing number 152 text elements constituting the element 15. In the initial complex linguistic LLK 15 11 offers no characterizing its unique name (VH) having the practical use. IPLLK sentences 11 is the borderline between linguistics and logic. From a linguistic point of view, IS LLK is a syntactic unit of the “syntactic construction” type, formed from a PLC by combining PLCs on the basis of the presence of direct syntactic subordination and composing links between the PLC. IS LLC consists of the number of PLC identified in the original sentence. The mentioned direct syntactic subordinate link means the presence between the elements of different PLC (between LLE different PLC) a syntactic subordinate link. A direct syntactic association means the presence between elements of different PLCs (between LLE different PLCs) a syntactic composing relationship. From the point of view of the syntax, IP LLK is a transformed original sentence without distorting its meaning. The essence of the transformation of the original linguistic sentence is that all the applied linguistic techniques (complications) aimed at simplifying the linguistic forms and structures of the author's assertions (denials) in the text of the linguistic sentence (for example, without limitation, the use of homogeneous members involved). ) cancel. Instead of the original linguistic sentence, they form an array of simple sentences that are syntactically and logically related to each other. The links mentioned are clarified and then recorded in one way or another. The need for such a transformation is relevant because simultaneously with the simplification of the linguistic forms and structure of the linguistic sentence, the use of the mentioned linguistic techniques leads to the complexity and ambiguity of the logical structure of the original linguistic sentence, to the complexity and ambiguity of the user’s sense of the original sentence, as well as to the great technical complexity of the correct intelligent machine analysis of the content of the original linguistic sentence. The original sentence thus transformed is (subject to the use of the mentioned techniques in the original linguistic sentence), in fact, a complex sentence consisting of transformed simple sentences in an amount greater than the number of initial simple sentences in the original linguistic sentence. However, unlike the original linguistic sentence, all transformed simple sentences in the LLK IS are unambiguous simple judgments (imaginable statements or denials). Registration of element 15 (IP LLK) in the form of a data structure (array of transformed PLC (elements 14)) allows revealing the multi-level syntactic structure of element 15 (IP LLK) and the connections between the elements of this structure. The levels of IP LLK reflect the structure of the syntactic subordinate connection between the structured PLC (SPLC) as constituent parts of the IC LLC and are due to the identified syntactic links between the component parts of element 15 (elements 14 of the linguistic sentence 11.) Element 15 (IP LLC) is formed from the mentioned structured PLC (SPLL) ) - elements 14. It is mandatory IP LLK contains only element 14 (SPLCK) of the first level (elements 13 of the first type). The presence of other elements 14 (SPLK) of the second and subsequent levels (elements 13 of the second and subsequent types) is due to the linguistic complications of the original linguistic sentence. The first level SPLC (elements of the first type 13) include PLC, which are not subject to simple sentences. The second-level SPLLK (elements of the second type 13) include PLCA, which are subject to simple sentences, provided that the first level SPLC are the main ones. The third level SPLK (elements of the third type 13) include PLCA, which are subject to simple sentences, provided that the second level SPLC is the main thing for them. These statements are thus also valid for the next levels of SPLC (fourth, fifth, sixth, and so on), and the possibility of the existence of such subsequent levels should be obvious to a person skilled in the art. The syntactic structure of the IC LLK 15, in addition to the syntactically subordinate SPLKK, may contain syntactic written SPLLK. At the same time, all SPLCMs of the first level (elements 13 of the first type) are necessarily composed of PLCMs with each other. Starting with the second level SPLKK (elements 13 of the second and subsequent types), the SPLK of the same level may or may not have syntactic composing links with each other. The syntactic composing relationship between SPLK in IS LLK is identified if the syntactically main words (LLE) have syntactically main OLLOs of such SPLLK of the same syntactic parent (syntactic main word that has a direct syntactic subordinate connection with such a word (LLE)). Additional conditions may be the presence of the main words (LLE) of such SPLLK of the same syntactic role, as well as the presence of an indication of a connection between such words (LLE), namely, a comma or a writing union. IP LLK 15, in contrast to the previously mentioned IP LLK 12 and PLC 13, can be only in the singular - only one LLK 15 can be formed from one initial linguistic sentence. From a logical point of view, IP LLK 15 is a logical entity expressing a complex judgment (non-quantifier judgment), which is a logical construction whose elements are simple judgments. The quantifier of a complex judgment is determined by its quantitative characteristic, that is, by the presence or absence of uniqueness in a complex judgment. According to the quantitative characteristic (quantification), all complex judgments can be divided into two categories: single-valued complex judgments and ambiguous complex judgments. Unambiguous complex judgments are quantifier complex judgments, in which the quantifier index is always defined and equal to one, that is, each element of a complex judgment has no variation, is always unequivocal. The unambiguity of a complex judgment is manifested by the presence of elements in a complex judgment that cannot be interpreted as variants of statements or denials, or as variants of the conditionality of the same statement or negation. An example of unambiguous complex judgment may be the following judgment: “If the buyer paid for the goods, then the goods must be transferred to the buyer by the seller.” This complex judgment does not allow for any variation - a simple judgment “the goods must be transferred to the buyer by the seller” is due to a single simple judgment “if the buyer paid for the goods”. Ambiguous complex judgments are quantifier complex judgments in which the quantifier index is always defined and is always greater than one, that is, at least one element of the complex judgment has variability. The ambiguity of a complex judgment is manifested by the presence in the composition of a complex judgment of elements that can be interpreted as variants of statements or denials, or as variants of the conditionality of the same statement or denial. An example of an ambiguous complex judgment may be the following judgment: “If the buyer paid for the goods, then the goods must be transferred to the buyer by the seller or the goods must be transferred to the buyer by another company official”. This complex judgment allows variability of the statement - either “the goods must be transferred to the buyer by the seller”, or “the goods must be transferred to the buyer by another official of the company”. A complex judgment consists of simple judgments having initial (established in the initial linguistic sentence) syntactic connections among themselves. Due to the fact that such links can be both syntactic subordinate links and syntactic composing links, it is impossible to guarantee the absence in a complex judgment of the variability of statements or negations, or the variability of conditionality of statements (negations). In connection with the foregoing, the ICLA is a complex judgment with an indefinite quantitative characteristic (the quantifier index can be either equal to one or be greater than one), and such a complex judgment is “non-quantifier”. From an analytical point of view, IS LLK is an information-filled scheme that clarifies the logical construction of a sentence (logical connections between individual simple judgments embedded in the original linguistic sentence). In this regard, the IC LLK is preferably shown in a non-linguistic textual form (in the form of a complex sentence consisting of a set of simple sentences without a coherent connection and implicated (adverbial) turns, in which there can be both a subordinate and a companion connection between the said simple sentences) , and in tabular or schematic form. The mentioned tabular or schematic form of the demonstration allows you to quickly and accurately understand and analyze all used basic logical entities (SPLLK) and all the logical connections between the mentioned logical entities of the original linguistic sentence. In particular, without limitation, such a developed and at the same time structured representation of the original linguistic sentence (a logically connected set of simple sentences without homogeneities) allows one to increase the processing efficiency of the linguistic sentence 11 by machine tools, because instead of one processed sentence with a complex structure, it is possible to process many simple sentences with identified logical connection between the elements of this set.

[154] The identification of the types of elements 13 of the ninth SMD data structure during step 3042 is made based on the results of identifying the values 2171 of the sixth part of the linguistic characteristics 217 of the text elements 21 constituting the PLLC 13. to carry out the following actions: in the first stage, from all PLCs 13, PLCs are chosen in which the main LLE of the main OLLO element 13 (PLCA) does not have a syntactic parent; such a PLC will be the element 13 of the first type - an obligatory element of the tenth data structure of the MD; in the second stage, from the remaining PLCs 13, the type of which has not yet been identified, select such PLCs in which the main LLE of the main OLLO element 13 (PLCA) has a syntactic parent in the PLCA identified as element 13 of the first type; such a PLC will be the element of the second type 13 - not a mandatory element of the tenth data structure of the MD; in the third and subsequent stages from the remaining PLC 13, the type of which has not yet been identified, select such PLC in which the main LLE of the main OLLO element 13 (PLC) has a syntactic parent in the PLC identified by element 13 of the second or subsequent species; such a PLC will be an element of the third or subsequent species 13 - not a mandatory element of the tenth data structure of the SMD. The presence of such PLCs is due only to the syntactic complexity of the original linguistic sentence. At the same time, an additional stage is the identification of the composing connections between elements 13 (PLC). PLC 13, in which there is no syntactic subordinate connection, but syntactic composing connection is identified, refer to the same type as PLC 13 with which it was composed. Elements 14 (constituent parts of element 15) of the tenth SMD data structure during step 3043 are identified by identification with elements 13 identified at stage 3042 as certain types of element 13. In this case, elements 13 of the first type are identified as element 14 of the first level, elements 13 of the second the species is identified as element 14 of the second level, and so on, elements 13 of the third and subsequent types are identified as element 14 of the third and, respectively, subsequent levels.

[155] The identification of the types of elements 13 of the ninth MDD data structure under step 3042 does not change the value 131 of element 13 and does not change the sequence numbers of the text elements 21 of the linguistic sentence 11 constituting element 13 (PLC). The value and sequence numbers of the TE element 14 (SPLLK) of the tenth SMD data structure in step 3043 are identified as follows: the values 211 of the text elements 21 of the linguistic sentence 11 constituting element 13 are identified as the value 141 elements 14 (SPLLC) and the sequence numbers 212 of the above-mentioned text elements 21 of the linguistic sentence 11, constituting element 13, are identified as sequence numbers 142 of text elements constituting element 14 (SPLLK). The identification of the value and sequence numbers of the TE element 15 (IP LLK) of the tenth data structure of the DMD in step 3043 is as follows: the values 211 of the text elements 21 of the linguistic sentence 11 constituting all elements 14 are identified as the value 151 elements 15 The sequence numbers 212 (of the mentioned textual elements 21 of the linguistic sentence 11, constituting all the elements 14, are identified as the sequence numbers 152 of the text elements making up the element 15 (IS LLK).

[156] The formation of the tenth data structure of the MDD during step 3043 is performed by combining in one data structure the elements of the 14th tenth data structure of the MDD and their identification data. In this case, the elements 14 that are combined in one data structure, being constituent parts of element 15, thus form element 15, which is the main element of the tenth data structure of the MDD. The combination of these elements and their identification data in one data structure is carried out according to principles and methods known from the prior art, which, respectively, are not described in further detail below. As a result, the tenth data structure of the SMD is an array (list) of structured PLCM (SPLLK) - elements 14 of the first and subsequent levels, located in the list of SPLCM, taking into account the increasing level of element 14 (and indicating this level), and also taking into account the increase of the text number the link element element of element 14 (and an indication of this sequence number), as well as the sequence number of the text element of the syntactic parent of element 14 (and an indication of this sequence number). At the same time, the first part of the ISLK and the first sequence number in the mentioned list of structured PLLCs will be SPLLK 14 without a syntactic parent and without a link sign. Elements 14 of the tenth SMD data structure are used to build a schema or table of logical links that visually display the logical construction of the original linguistic sentence (logical links between individual simple judgments embedded in the original linguistic sentence). In particular, without being limited, as it was mentioned earlier with reference to elements 15, such a developed and at the same time structured representation of the original linguistic sentence (a logically connected set of simple sentences without homogeneity) allows increasing the processing efficiency of the linguistic sentence 11 by machine tools, because instead of a single sentence being processed with a complex structure, it is possible to process many simple sentences with an identified logical connection between elements of this set.

[157] The identification of the linguistic characteristics of the TEs that make up element 15 (IS LLK) of the tenth data structure of the DMD, and their values, if necessary, is produced by organizing a query in the BDLP, formed as part of step 3041, consisting of the identity data of the TEs that make up element 15 (IS LLK ), and obtaining the values (2131, 2141, 2231, 2151, 2161, 2171) of all parts of the linguistic characteristics (213, 214, 223, 215, 216, 217) of textual elements 21 of the linguistic sentence 11, of which element 15 consists (IC LLK ). At the same time, as described earlier, the linguistic features of element 15 (IP LLK) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which elements 15 consist (IC LLK).

[158] FIG. 36, by way of example, but not limitation, depicts a general scheme for performing the steps of step 305 of forming the eleventh UDL data structure, which is the third UDT data structure for the method 300 under consideration. for the presence in ISLK of composed PLCs, on which the first and second types of element 15 identify the tenth SMD data structure, as well as the identification of non-transformed elements 16 of the eleventh SM data structure D and their identification data, representing for each non-transformed element 16, as an example, but not limitation, the value 161 of non-transformed element 16 of the eleventh data structure of the SMD and the sequence numbers 162 TE of the linguistic sentence 11 constituting the non-transformed element 16; performing step 3052 of generating transformed elements 16 of the eleventh SMD data structure, wherein transformed elements 16 of the eleventh SMD data structure of the second type of elements 15 are formed, as well as identification data of the transformed elements 16, representing for each transformed element 16, as an example, but not restrictions, the value 161 of the transformed element 16 of the eleventh data structure of the MDD and the sequence numbers 162 TE of the linguistic sentence 11 constituting the transformed elements nty 16; the execution of step 3053 of forming the eleventh data structure of the DMD, which forms the eleventh data structure of the SMD of the converted elements 16 of the eleventh data structure of the SMD or of the untransformed element 16 of the eleventh data structure of the SMD.

[159] FIG. 37, by way of example, but not limitation, depicts the general structure of the eleventh UDB data structure that is the fourth UDT data structure for the present conversion method 300. The eleventh UDD data structure is a UDT containing 16 elements of the 11th UDB data structure, which are complex linguistic-logical constructions (SLLC) of linguistic sentence 11 and the identification data of LogO, representing for each element 16, as an example, but not limitation, 161 elements 16 of the eleventh data structure of the SMD and sequence numbers 162 of text elements constituting element 16. The SLCA of the linguistic sentence 11 does not have any unique characterizations (UN) that have practical use. In the data structure, elements 16, by way of example, but not limitation, may be referred to as “SLLK1”, “SLLK2”, “SLLK3”, “SLLKn”, where n ≥ 1 is the ordinal number of the element in the linguistic sentence. The SLCA of the linguistic sentence 11 is the borderline between linguistics and logic. From a linguistic point of view, SLLC is a syntactic unit of the form “syntactic construction”, formed from an ISLK by heterogenization of an ICLL. From the point of view of syntax, SLK is a separate simple sentence (if the original linguistic sentence is a simple sentence without syntactic complications (homogeneous members, revolutions, etc.)) or a complex subordinate sentence that does not contain homogeneous members (the words between which have a syntactic composing relationship). From a logical point of view, SLLK is a logical entity expressing a complex judgment (quantifier judgment), which is a complete logical construction of thinking, through which the thought that something (predicate judgment) is affirmed or refuted about the subject matter of judgment (subject judgments). The difference between SLCK and ISLK in the quantifier of complex judgment. If IS LLK admits the possibility of having ambiguity in a complex judgment, then SLLC (having a quantifier of one) is an absolutely single-valued complex judgment. SLCK cannot contain several homogeneous (composed) simple judgments. In SLC, there can be no ambiguity either in approving (denying) something, or when the approval (refutation) is conditional, or when the approval (refutation) elements are conditional, regardless of the composition and design of the original linguistic sentence.

[160] The identification of the type of IP LLK 15 in step 3051 is made by analyzing the values of the linguistic characteristics of the text elements constituting the IP LLK 15, in order to identify the syntactic composing connections between SPLLK 14 in the IP LLK 15. The syntactic composing link between SPLLK 14 is identified if the syntactically main LLE of the syntactically main OLLO of such SPLLKs of the same syntactic parent (the syntactically main LLE of another SPLLK, which with the word (LLE) in the composed SPLLK has direct syntax eskaya subordinate connection). Additional conditions may be the presence of the main LLE main OLLO mentioned penned SPLLK of the same syntactic role, as well as the presence of a sign of connection between the mentioned penned LLE, namely, a comma or a writing union. When identifying a syntactic somatic connection between the main LLE main OLLOs of two or more SPLLKs, such an LLK is identified as the second type of element 15. LLK 15, which does not identify the syntactic somatic connection of the main LLE of the main OLLO to the SPLLK, is identified as the first type of the 15. element. In this, the identified first type of element 15 of the tenth SMD data structure is identified with the non-transformed element 16 of the eleventh SMD data structure. The formation of the transformed elements of the eleventh data structure of the DMD (transformed elements 16 obtained from the second type of elements 15) at step 3052 is made on the basis of the syntactic composing relationship identified between SPLLK identified at step 3051 by converting the second type of LLK. The meaning of the transformation of an IP LLK of the second type at step 3052 is to heterogenize the IP LLK, that is, to eliminate syntactic homogeneities in the IP LLK by forming from the second type element 15 a set of new IP LLKs identical in homogeneity to the element 15 of the first type. Moreover, each new LLK of the mentioned set may contain only one of the mentioned SPLCM with homogeneous members (if the LLM IP of the second type contains one row of homogeneous members) or only one unique combination of the mentioned SPLCM with homogeneous members of different rows of homogeneous members (if the LLK of the second kind contains several rows of SPLK with homogeneous members). Many IP LLK, formed from IP LLK (element 15) of the second type are heterogeneous SLLK (transformed elements 16), that is, formed from one LLK IP of the second type by its heterogeneous transformation (heterogenization). The process of heterogenization of IP LLK (element 15) of the second type can be carried out, by way of example, but not limitation, as follows: at the first stage, rows of homogeneous members in element 15 of the second type are identified; in the course of identifying the series of homogeneous members, they themselves identify the series of homogeneous members and the sequence numbers of homogeneous members in the series, as well as signs of the connection of each homogeneous member; at the second stage, chains of homogeneous members are detected for each SPLLL identified, containing the LLE-POC (SPLCP-POC) element 15 of the second type; A chain of homogeneous members (an ECH chain) is a SPLLK-POC and a dependent chain of homogeneous members (a chain of syntactically related SPLLK, starting from the first syntactic descendant of homogeneous members (syntactically dependent SPLLK) and continuing along the chain of syntactic dependence (on syntactic subordinate link) to another SPLLK -OCH or up to the last PLC in the element 15 of the second type; the identified PTS chains are classified by the fact that there is a syntax descendant of LLE in the dependent PTS chain that is not included in the dependent PTS chain; those PTS chains that have dependent PTS chains without a syntactic descendant beyond the dependent chain of homogeneous members are considered extreme chains of homogeneous members (extreme chains of PTS), and those PCH chains that have dependent chains of POC with a syntactic descendant beyond the dependent chain of PTS, are considered internal chains of homogeneous members (internal chains of OFC); in the third stage, PLLCs of element 15 of the second type are identified that are not included in the chains of homogeneous members (PLCs outside the chains of RCh); in the fourth stage, replaceable dependent chains (interchangeable replacement centers) of the element 15 of the second type are formed; replaceable SC is the basis of the transformed elements 16, consisting of one extreme chain of PSh and internal chains of PS, if such internal chains of PS are along the chain of a continuous syntactic subordinate connection between the extreme chain of PS and PLC outside the chains of PS; at the fifth stage, heterogeneous SLCAs are formed (elements 16); heterogeneous SLLC is formed from one interchangeable SCC and PLC outside the PTS chain (if there are such PLCs); the number of interchangeable replacement elements of the element 15 of the second type determines the number of heterogeneous SLCAs formed from one element 15 of the second type.

[161] The identification of the types of elements 15 of the tenth data structure of the MDD within step 3051 does not change the value 151 of elements 15 and does not change the sequence numbers of the text elements 21 of the linguistic sentence 11 constituting element 15 (IS LLK). The identification of the value and sequence numbers of the TE of the non-transformed element 16 (SLLC) of the eleventh SMD data structure as part of step 3051 is as follows: the values 211 of the text elements 21 of the linguistic sentence 11 constituting the element 15 of the first type of the tenth data structure of the SMD are identified as the value 161 of the non-transformed element 16 (SLCK), and the ordinal numbers 152 of the above-mentioned text elements 21 of the linguistic sentence 11, constituting element 15 of the first type, of which the non-transformed element 16 consists, identify as sequence numbers 162 text elements constituting non-transformed element 16 (SLCK). The meaning and sequence numbers of the transformed element TE 16 (heterogeneous SLLC) of the eleventh SMD data structure in step 3052 are identified as follows: 211 text elements 21 of the linguistic sentence 11 constituting element 15 of the second type of the tenth SMD data structure, except for 211 text elements 21 linguistic sentences 11 that make up separate parts of the element 15 of the second type (SPLLK-RN), which were removed during heterogenization, and signs of the connection of the remote RLLC-RN (syntak sically subordinate remote allorders or punctuation marks) are identified as the value 161 of the transformed element 16 (SLLC), and the ordinal numbers 212 of the text elements 21 of the linguistic sentence 11 constituting the element 15 of the second type of the sixth data structure of the MD, except for the ordinal numbers 212 text elements 21 of the linguistic sentence 11, constituting separate parts of the second type element 15 (SPLLK-RCh), which were removed during heterogenization, and the connection signs of the deleted SPLLK-RCh (syntactically dchinennye remote SPLLK-OCH coordinative associations or punctuation) is identified as sequence numbers 162 text elements constituting the converted element 16 (heterogeneous SLLK).

[162] The formation of the eleventh data structure of the MDD in step 3053 is performed by combining in one data structure identified in steps 3051 and 3052 elements 16 of the eleventh data structure of the DMD, as well as their identification data according to principles known from the prior art and further not described in detail. The first of the merged elements of the eleventh data structure of the MDD is the first type element identified at step 3051 of the first type, which is the untransformed element 16, i.e. SLLK 16, coinciding with the IS LLK 15 without syntactic composing. The second of the combined elements of the eleventh data structure of the SMD is the transformed elements 16, formed at step 3052 as a set of transformed elements 16, which are heterogeneous SLLC, formed from the element 15 of the second type (IP LLK with syntactic linking) by the second type.

[163] The linguistic characteristics of the TEs that make up element 16 (SLLC) of the eleventh SMD data structure and their values, if necessary, are identified by organizing a query in the BDLP, formed as part of step 3041, consisting of the identification data of TEs that make up element 16 (SLLC), and obtaining the values (2131, 2141, 2231, 2151, 2161, 2171) of all parts of the linguistic characteristics (213, 214, 223, 215, 216, 217) of the textual elements 21 of the linguistic sentence 11, of which element 16 consists (SLLC). At the same time, as described earlier, the linguistic features of element 16 (SLCA) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which the elements 16 consist (SLLC).

[164] However, after completing the previously described step 301, in order to provide an alternative to improve the accuracy of subsequent search in a structured dataset (SMD), it becomes alternatively possible to further convert the SMD containing at least the main linguistic objects ( OLLO) linguistic sentences and their identification data. In this case, it will be obvious to a person skilled in the art that the principles and methods described below upon completing the previously described step 301 of the method 300 can be carried out simultaneously (in parallel) with the previously described steps 301-305 of the method 300, and not simultaneously (alternatively or sequentially). , including regardless of the order), and also that the individual principles and methods of the individual steps described below can be implemented in a similar way.

[165] FIG. 38, by way of example, but not limitation, depicts a general scheme for performing the steps of the claimed method 400 for converting an SMD containing at least the main linguistic-logical objects (OLLO) of the linguistic sentence and the identification data of the OLLO, which is the initial data structure for the method 400 in question The claimed method 400 for converting an SMD containing at least an OLLO linguistic sentence and its identification data is characterized by: performing an identification step 301 suitable for converting data structure that contains an OLLO, which identifies an MDD data structure that contains elements of the aforementioned convertible data structure that contains an ALLO, which is the original data structure of the MDD within the framework of this method 400, and these elements are suitable for transforming the data structure logical objects (OLLO) linguistic sentences and identification data OLLO; the step 402 of forming the twelfth data structure of the MDD, which forms the twelfth data structure of the MDD, which is the first data structure of the MDD data for the method 400, containing the elements of the said twelfth data structure of the MDD, OLE) linguistic sentences formed by dividing OLLO into semantic parts of OLLO, and also represent the identification data of OLLE, representing for each OLLE, as an example, but not limiting: the OLLE value and the ordinal (ordinal) number (s) of the TE language of the linguistic sentence constituting the OLLE; the step 403 of forming the thirteenth data structure of the MDD, which forms the thirteenth data structure of the MDD, which is the final data structure of the MDD data for the method 400, containing the elements of the thirteenth data structure of the MDD, and these elements of the thirteenth data structure of the MDD are the original linguistic elements ( ILE) of the linguistic sentence, formed by dividing the OLE into the semantic parts of the OLE and forming the original elements from them, as well as vlyayut a ILLE identification data representing each ILLE, as an example, but not limited to: ILLE value and serial (serial) number (s) TE linguistic supply components (components) ILLE.

[166] As previously indicated with reference to FIG. 26, by way of example, but not limitation, shows the general scheme for performing step 301 of identifying an SMD data structure, which identifies the data structure of an SMD, which is the initial data structure for the method 400 in question, whose elements 91 represent the OLLO linguistic sentence 11, as well as the identification data of elements 91, representing for each element 91, as an example, but not limitation, the value of 911 element 91 and the ordinal number of the linguistic sentence 11 constituting (constituting) the element 91. Described in this way with reference to FIG. 26 The process is not described further in detail. Based on the results of step 301, the data structure shown in FIG. 27, the composition of which is described with reference to FIG. 27, respectively, is not described further below.

[167] FIG. 39, by way of example, but not limitation, shows the general scheme for performing the steps of step 402 of forming the twelfth SMD data structure, which is the first data structure for the method 400 in question. Step 402 is characterized by: performing step 4021 of generating values 2181 of the seventh part of linguistic characteristics 218 of elements 21, constituent elements 91 of a data structure suitable for transformation, containing an OLLO on which forms the values 2181 of the seventh part of the linguistic characteristics 218 elements 21 constituting the elements 91 and contribute the information to the BDLP of textual elements 21 of the linguistic sentence 11, which is formed in the framework of step 3041, forming as a result the BDLP of the text elements 21 of the linguistic sentence 11, which is being formed in the framework of step 4021; performing step 4022 of forming the semantic parts of the elements 91 of a data structure suitable for converting the OLLO, on which the first and subsequent (second, third, and so forth in order) semantic parts of the OLLO are formulated, clarifying the OLLO semantic structure; performing step 4023 of forming the twelfth data structure of the DMD, which identifies the elements 17 of the twelfth data structure of the DMD, as well as the identification data of the elements 17, representing for each element 17, as an example, but not limitation, the value 171 of the element 17 of the twelfth data structure of the MDD and ordinal (s) number (s) 172 TE linguistic sentences 11, constituting (making) element 17, and form the twelfth data structure of the SMD.

[168] FIG. 40, by way of example, but not limitation, depicts the general structure of the linguistic characteristics database (BDLP) formed within step 4021, which is the BDLP text elements 21 of sentence 11 contained in the elements 91 suitable for transforming a data structure containing an OLLO formed within stage 4021. BDLP, formed under stage 4021, differs from BDLP, formed under stage 3021, the presence of values 2181 of the seventh part of the linguistic characteristics 218, indicating the main word of the semantic part of the element 91 (OLLO). The reason for identifying the main word of the semantic part of OLLO is that, using the identified main word of the semantic part of OLLO and the previously identified syntactic links between words (LLE) in OLLO, OLLO can be divided into separate semantic parts. The semantic parts of OLLO clarify the semantic structure of OLLO, in which the individual parts perform their limited semantic roles in OLLO. The semantic parts in OLLO allow identifying in OLLO the dominant and clarifying entities of the surrounding world (objects and actions) integrated in it for the correct identification of their semantic roles and, as a result, the meaning of OLLO. Selection of separate semantic parts in OLLO allows you to establish their unique logical role in OLLO, which allows you to store these parts separately without losing their semantic logical role in the sentence. Such separate storage allows for a quick and accurate search for the semantic parts of OLLO, as well as, separately from other parts of the linguistic sentence, to produce various kinds of analysis and processing.

[169] The formation of the seventh part of the linguistic characteristics 218 and their values 2181 during step 4021 is carried out on the basis of a comprehensive analysis of the values of the linguistic characteristics of the text elements 21 included in the elements 91. During this analysis, all the text elements 21 that make up the element 91 are checked for the main word of the semantic part of the element 91. A sign of the main word of the semantic part of the element 91 may be, as an example, but not limitation, the presence of the following lingual values in the text element (TE) historical characteristics: TE is the main word OLLO or TE has dependent TE in the form of a preposition. Other own criteria for identifying the syntactic part of OLLO can be pre-set. For example, without being limited to, the list of parts of speech that indicate the main word of the syntactic part of OLLO can be specified. If TE has the indicated values of linguistic characteristics, the corresponding values 2181 of the seventh part of the linguistic characteristics 218 form - “the main word of the semantic part of OLLO”.

[170] Formed at the end of step 4021, the values 2181 (the main word of the semantic part of element 91) of the seventh part of the linguistic characteristics of 218 elements 21 constituting OLLO 91 suitable for transforming the data structure containing OLLO are inserted into BDLP of textual elements 21 of linguistic sentence 11, formed within step 2031, forming as a result BDLP text elements 21 of the linguistic sentence 11, formed in the framework of step 4021. All parts (211, 214, 232, 215, 216 and 218) of the linguistic characteristics of the text elements 21 of the lingua The classical sentences 11 and their meanings (2111, 2141, 2321, 2151, 2161, and 2181) form the unique linguistic attributes of the elements 91 for an alternative way to improve the accuracy of searching in a structured dataset.

[171] FIG. 41, by way of example, but not limitation, shows the general structure of the formed twelfth SMD data structure, which is the first for the present conversion method 400. The twelfth SMD data structure is the SMD containing elements 17 of the twelfth SMD data structure, which are the main linguistic-logical elements (OLE) of the linguistic sentence 11 and the OLE identification data, representing, by way of example, but not limitation, the values of 171 elements 17 of the twelfth data structure and oryadkovye number 172 text elements constituting OLLE. OLE 12 linguistic sentences 11 are absent characterizing their unique names (UN), which have practical use. In the data structure, elements 12, by way of example, but not limitation, may be referred to as “OLL nm”, where n ≥ 1 indicates the OLLO sequence number in the linguistic sentence, and m ≥ 1) indicates the OLLO syntactic level, starting with first. OLL sentences 11 - is the borderline between linguistics and logic. From a linguistic point of view, OLLE is a syntactic unit of the “syntactic construction” type, formed from OLLO 91 by separating 91 syntactic parts into OLLO based on the presence of the main words of the syntactic parts in OLLO 91. The above main words of the syntactic part of OLLO 91 are such parts speeches as a noun, pronoun or verb (in any grammatical form), which are either syntactically the main word OLLO 91, or contain a direct syntactic descendant (a word with which direct syntactic subordinate connection) with the syntax role “preposition”. Other criteria for identifying the syntactic part of OLLO 91 can be pre-set. For example, without limitation, it is possible to set criteria in the form of a specific list of prepositions whose presence indicate the main word of the syntactic part of OLLO 91. From the point of view of the syntax, OLLE 17 is words and special phrases inside OLLO 91. Depending on the complexity of the linguistic structure of OLLO 91, it is possible to single out one or several OLLE 17. In its logical point of view, OLLE 17 is a logical entity that is a logically separable part element of simple judgment. Moreover, such logically separable parts do not differ in any way from OLLO 91 due to the fact that, like OLLO 91, they represent a conceivable (semantic) image of a certain object or action of the surrounding world). The reason for the existence of semantic parts of the image of OLLO 91 is that not every image of OLLO 91 can be linguistically realized using only one component element (a group of words without a preposition between words). For example, without being limited to, the conceivable image of OLLO 91 on the right to something (for example, not limited to, “the consumer’s right to return goods”) cannot be realized by one component element (one group of words without a preposition between words)). In the example mentioned, only two constituent elements — the first — the “consumer right” and the second — the “return of goods” —constitute a conceivable image of the element of simple judgment. The constituent element of OLLO 91 (the semantic part of OLLO) is called the term OLLO 91. From a semantic point of view, the terms OLLO 91 that form OLLO 91 are not the same, that is, they have different semantic roles. Syntactically, the main terms OLLO 91 have the maximum semantic role, that is, they are the terms OLLO 91 of the first semantic part. The term OLLO 91 of the first semantic part defines the semantic vector OLLO 91. For example, not limited to, in the example “consumer's right to return goods”, the semantic essence of the image of OLLO 91 is formed by the constituent element “consumer right”, and not the constituent element “return of goods”. The terms OLLO of the second and subsequent semantic parts are syntactically dependent terms of OLLO 91, and their presence in OLLO 91 is necessary only to refine the conceivable image of OLLO 91. The more complex the conceivable image of OLLO 91, the more terms of the OLLO 91 may require clarification of its conceivable image. Structuring the terms of OLLO 91 as semantic parts of OLLO allows you to correctly perceive the semantic roles of individual terms in OLLO 91. Separating in this way OLLO 91 allows you to perform an intelligent search for information with increased accuracy, since if you have a more structured (by the logical role of words) data array, it is possible to more accurately description of the desired objects. As a result of the machining of such a data array, the accuracy of the search is increased and the search time is reduced

[172] The formation of parts (semantic parts) of elements 91 of a data structure that can be converted to an OLLO is processed at step 4022 by performing the following actions: at the first stage, from the identified main word of the semantic part of OLLO 91, all syntactically subordinate words are identified, up to the word, which is itself the main word of the semantic part of OLLO 91, but not including this word; at the second stage, the main word of the semantic part of OLLO 91 and all the mentioned syntactically subordinate words, including consecutively subordinate, form the semantic part of OLLO 91. The sequence number of the semantic part in OLLO indicates its semantic role in OLLO and is formed in accordance with the sequence number of the text element (TE) of the main word of the semantic part of OLLO 91. The semantic part of OLLO 91 with the lowest sequence number TE of the main word is the first semantic part of OLLO 91. The semantic part of OLLO 91, and The nearest TE TE number of the main word of the semantic part is the second semantic part of OLLO 91, and so on. The serial number of the OLE is indicated in the name of the OLE, for example, but not limited to - “OLE 1.2”. Such a name of element 17 indicates that it is the second semantic part in the first OLLO (according to the syntactic level “.2”). The identification of the elements 17 of the twelfth data structure of the MDD during step 4023 is made on the basis of the step 4022 of forming the semantic parts of the elements 91 suitable for transforming the data structure containing the OLLO. All formed semantic parts of elements 91 identify with elements 17 of the twelfth data structure of the MDD.

[173] The meaning and sequence numbers of the TE element 17 of the twelfth SMD data structure are identified in step 4023 by identifying the value 171 elements 17 with the 911 values of the identified semantic part of element 91, and the sequence numbers 172 of text elements 21 that make up element 17 by identifying with sequence numbers 912 text elements constituting the identified semantic part of the element 91.

[174] The formation of the twelfth SMD data structure during step 4023 is performed by combining in one data structure elements 17 of the twelfth SMD data structure and their identification data according to principles and methods known from the prior art, which, respectively, are not described in further detail below.

[175] Identification of linguistic characteristics of TE, constituting elements 17 (ALEE) of the twelfth data structure of the DMD and their values, if necessary, is produced by organizing a query in the BDLP, formed under step 4021, consisting of the identification data of TE, constituting element 17 (OLE), and obtaining the values (2131, 2141, 2231; 2151, 2161, 2181) of all parts of the linguistic characteristics (213, 214, 223, 215, 216.218) of the text elements 21 of the linguistic sentence 11, of which the element 17 consists (OLLE). At the same time, as described earlier, the linguistic features of the elements 17 (OLE) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which the elements 17 consist (OLLE).

[176] FIG. 42, by way of example, but not limitation, shows a general scheme for performing the steps of step 403 of forming the thirteenth data structure of the SMD data, which is the second data structure for the method 400 in question. Step 403 is characterized by: performing step 4031 of forming 2191 values of the eighth part of linguistic characteristics 219 of elements 21, constituting elements 17 of the twelfth data structure of the MDD, on which the values 2191 of the eighth part of the linguistic characteristics 219 of the elements 21 constituting the elements 91 are formed and contribute the resulting information I BDLP text elements 21 linguistic Proposition 11, formed in 4021 under the stage, forming eventually BDLP text elements 21 linguistic Proposition 11, formed in 4031 under the stage; step 4032 of forming the semantic parts of the elements 17 of the twelfth data structure of the MD, which forms the first and next (second, third, and so on in order) semantic parts of OLE, clarifying the semantic structure of OLLE; performing step 4033 of forming the elements 18 of the thirteenth data structure of the DMD, which forms the elements 18 of the thirteenth data structure of the MDD and the identification data of the elements 18, representing, by way of example but not limitation, the values 181 of the elements 18 of the thirteenth data structure of the DMD, serial numbers 182 TE linguistic sentences 11, constituting elements 18, and also identify the first and second types of elements 18 of the thirteenth data structure of the SMD and form the thirteenth data structure of the SMD.

[177] FIG. 43, by way of example, but not limitation, shows the general structure of the linguistic characteristics database (BDLP) formed during step 4031, which is the BDLP text elements 21 of sentence 11 contained in elements 17 of the twelfth data structure of the MDD. BDLP, formed under stage 4031, differs from BDLP, formed under stage 4021, by the presence of 2191 eighth parts of linguistic characteristics 219, indicating the main word of the semantic part of the element 17 (ALLE). The reason for identifying the main word of the semantic part of OLE is that, using the identified main word of the semantic part of OLE, and the previously identified syntactic links between words (LLE) in OLLE, OLLE can be divided into separate semantic parts. The semantic parts of the OLEE clarify the semantic structure of the OLEE, in which the individual parts fulfill their limited semantic roles in the OLEE. The semantic parts in the OLEE make it possible to isolate in the OLEE the dominant and specifying entities of the surrounding world (objects and actions) integrated into it for the correct identification of their semantic roles and, as a result, the OLEE meaning. Selection of separate semantic parts in OLEE allows you to establish their unique logical role in OLEE, which allows you to store these parts separately without losing their meaningful logical role in the sentence. Such separate storage allows for a quick and accurate search for semantic parts of the ALE, as well as separate analysis and processing of them from other parts of the linguistic sentence.

[178] The formation of the eighth part of the linguistic characteristics 219 and their values 2191 during step 4031 is carried out on the basis of a comprehensive analysis of the values of the linguistic characteristics of the text elements 21 included in the elements 17. During this analysis, all the text elements 21 that make up the element 17 check for the presence the main word of the semantic part of the element 17. The sign of the main word of the semantic part of the element 17 may be, as an example, but not limitation, the presence of the following text values (TE) of the lingual historical characteristics: TE is the main word OLEE or TE has the form of a noun, pronoun or verb (in any grammatical form). Other own criteria for identifying the syntactic part of the ALE can be pre-set. For example, without limitation, the list of parts of speech that indicate the main word of the syntactic part of the ALE may be specified. If the TE has the indicated values of linguistic characteristics, the corresponding values 2191 of the eighth part of the linguistic characteristics 219 form - “the main word of the semantic part of ALLE”.

[179] Formed according to the results of step 4031, the values 2191 (the main word of the semantic part of element 17), the eighth part of the linguistic characteristics 219 elements 21 constituting the OLE 17 of the twelfth data structure of the MDD are inserted into BDLP of the text elements 21 of the linguistic sentence 11, formed in the framework of step 4021, forming as a result, the BDLP of textual elements 21 of the linguistic sentence 11, formed in the framework of step 4031. All parts (211, 214, 232, 215, 216, 218, 219) of the linguistic characteristics of the textual elements 21 of the linguistic sentence 11 and values (2111, 2141, 2321, 2151, 2161, 2181, 2191) form features unique linguistic elements 17 for an alternative method of increasing search accuracy in a structured dataset.

[180] FIG. 44, by way of example, but not limitation, depicts the general structure of the formed thirteenth data structure of the DMD, which is the second data structure of the MDD for this conversion method 400. The thirteenth data structure of the MDD is a DMD containing elements 18 of the first and second types of the thirteenth data structure of the MDD, which are the initial linguistic-logical elements (ILE) of the linguistic sentence 11 and the ILE identification data, which for each ILLE, as an example, but not limited cheniya: the value of 181 element 18 SMD sixth data structure, sequence (serial) number (s) 182 TE linguistic Proposition 11, the constituent elements 18. ILLE 18 Linguistic offers 11 no characterizing their unique names (UN), with practical use. In the data structure, elements 18, by way of example, but not limitation, may be referred to as “ELEE nmk”, where n ≥ 1 indicates the sequence number of OLLO in the linguistic sentence, and m ≥ 1 indicates the syntactic level of OLLO in OLLO, starting with the first , and k ≥ 1 indicates the syntactic level of the ELEE in the ALE, starting with the first one. ILLE 18 sentences 11 is the borderline between linguistics and logic. From a linguistic point of view, ILLE 18 is the primary syntactic unit, which is a word. From a logical point of view, ILLE 18 is a logical entity that is a logically separable part of the term of the element of simple judgment (the term OLLO). Moreover, such logically separable parts do not differ in any way from OLE 17 due to the fact that, like OLE 17, they represent a conceivable (semantic) image about some object or action of the surrounding world). The reason for the existence of syntactic parts of ALE 17 is that not every conceivable image of ALE 17 can be represented using only one “source element” (a word expressing an object or an action). For example, without being limited to, the conceivable image of OLE 17 on the rights of someone, for example, without being limited to “consumer rights”, cannot be realized by a single initial element. In the mentioned example, only two initial elements - the first - “rights”, and the second - “consumer” - form the conceivable image of the term of the element of simple judgment (the term OLLO). The original element OLLE 17 is referred to as the concept of the term OLLO (PT OLLO) or elements 18 (ILLE). From a semantic point of view, PT OLLO (ILE 18), forming the term OLLO (ALLE 17) are unequal, that is, they have different semantic roles. Syntactically, the main PT OLLOs have the maximum semantic role, that is, they are the PT OLLO of the first semantic part. PT OLLO of the first semantic part defines the semantic vector of the term OLLO (OLLE 17). For example, in the example mentioned, “consumer rights” are the essence of the image of the term OLLO (OLLE 17) - namely “rights”, and not “consumer”. PT OLLO of the second and subsequent semantic parts (syntactically dependent PT OLLO) in the term OLLO (OLLE 17) is needed to clarify the meaning of the term OLLO (OLLE 17). The more complex the conceivable image of the term OLLO (OLE 17), the more PT OLLO (ILLE 18) it may require. Structuring of PT OLLO (ILLE 18) as semantic parts of OLE 17 allows one to correctly perceive the semantic roles of individual PT OLLO (ILLE 18) in terms of OLLO (OLLE 17). Element 18 (ILE) is formed from OLE 17 by selecting in the OLE 17 separate syntactic parts based on the presence of the main words of the syntactic parts of OLE 17 and the subsequent structuring of the text elements of the syntactic part. Depending on the complexity of the linguistic structure of OLE 17, it is possible to single out one or several syntactic parts (ILLE 18). The syntactic part (ILLE 18) of the ALE 17 may consist of only one mentioned main word or several syntactically related words (meaningful parts of speech), syntactically the main one of which is the said main word. Thus, the main word of the syntactic part (ILE 18) of OLE 17 is identified with the element 18 of the first type, and all the words that are syntactically dependent on it (meaningful parts of speech), if any, are identified with the element 18 of the second type. From a logical point of view, the original lingvo-logical elements (elements 18) of the first kind are “concepts” - that is, objects or actions of the surrounding world, and elements 18 of the second type are “signs of the concept”, that is, certain semantic characteristics of the mentioned objects and actions.

[181] The formation of parts (semantic parts) of elements 17 of the twelfth SMD data structure, at step 4032, is performed by performing the following actions: at the first stage, from the identified main word of element 17 (OLLE), all syntactically subordinate words are identified, up to a word that is itself the main word of the semantic part of the element 17 (AULE), but not including this word; at the second stage, the main word of the semantic part of the element 17 (ALEE) and all the syntactically subordinate words mentioned, including successively subordinate words, form the semantic part of the element 17 (ALEE). The sequence number of the semantic part in the OLE, indicates its semantic role in the OLE, and it is formed in accordance with the text element number (TE) of the main word of the semantic part of the OLE 17. The semantic part of the OLL 17 with the smallest TE number of the main word is the first semantic part of the element 17 (OLE). The semantic part of OLE 17, which has the TE number of the main word of the semantic part closest to it, is the second semantic part of OLL 17, and so on. The serial number of ILLE is indicated in the name of OLEE, for example, but not limited to - “ILLE 1.2.1”. This name of element 18 suggests that it is the first semantic part in the second OLLE of the first OLLO. The formation of elements 18 of the thirteenth data structure of the MDD during step 4033 is based on the results of step 4032 of forming the semantic parts of elements 17 of the twelfth data structure of the MDD as follows: at the first stage, all significant parts of speech in the semantic parts of the elements 17 are identified with elements 18 of the thirteenth data structure of the MDD; at the second stage, the mentioned identified main words of the semantic parts of the elements 17 are identified with the elements 18 of the first type; in the third stage, all other elements 18 of this semantic part, except for the element 18 of the first type, are identified with elements 18 of the second type.

[182] The identification of the value and ordinal (ordinal) number (s) of the TE element 18 of the twelfth data structure of the DMD is performed within step 4033 by identifying the value 181 of element 18 with the value (values) 211 of the text (text) element (s) 21 of the linguistic sentence 11, constituting (constituting) element 18, and ordinal (ordinal) number (s) of 182 text (s) element (s) 21 constituting (constituting) element 18 by identifying with ordinal (ordinal) numbered (s) 212 textual about (text) element (s) 21, constituting (making) element 18. Identifying the types of elements 18 of the twelfth SMD data structure in step 4031 does not change the value 181 of element 18 and does not change the ordinal number (s) of TE 21 linguistic sentence 11 constituting (constituting) the element 18 (ILE).

[183] The formation of the thirteenth data structure of the MDD during step 4033 is performed by combining in one data structure the elements of the first and second types of the thirteenth data structure of the MDD data, as well as their identification data according to the principles and methods known from the prior art, which, respectively, are described later in detail not described.

[184] The identification of the linguistic characteristics of the TEs that make up the elements 18 (ILE) of the thirteenth data structure of the MD and their values, if necessary, is produced by organizing a request to the BDLP, formed under step 4031, consisting of the identification data of the TEs, constituting element 18 (ILE), and obtaining the values (2131, 2141, 2231; 2151, 2161, 2181, 2191) of all parts of the linguistic characteristics (213, 214, 223, 215, 216, 218, 219) of the text elements 21 of the linguistic sentence 11, of which element 18 consists (ILE ). At the same time, as described earlier, the linguistic features of elements 18 (ILEE) are at least the morphological, syntactic and semantic characteristics of the text elements 21 of the linguistic sentence 11, of which the elements 18 (ILE) consist.

FIG. 45 illustrates, by way of example, but not limitation, an exemplary diagram of a system 500 for converting a structured data array, which in a preferred embodiment contains at least one or more computer devices 501 for converting a structured data array containing at least one or more than 5011 processors and 5012 memory. The structured dataset conversion devices 501 may include, but are not limited to: a personal computer, a portable computer p, tablet PC, PDA, smartphone, PHABLET and the like. The memory (machine-readable storage medium) 5012 of a structured data transformation device 501 comprises program code, which, when executed, causes said one or more processors 5011 of said device 501 to perform the actions of previously described methods for converting a structured data array. In some cases, the computing device 501 may be a server computing device associated with a user computing device configured to transmit commands or instructions to the server computing device 501 that cause the processor or processors 5011 of the server computing device to execute program code, which when executed by the server processor or processors computer device 5011 induces the processor or processors 5011 of the server computer device to perform action of any of the ways described earlier conversion structured dataset. The user computer device 502 may be, but is not limited to: a personal computer, a laptop computer, a tablet computer, a pocket computer, a smartphone, a phablet, a thin client, and the like. The user computing device 502 may be connected to the server computing device 501 via a wired or wireless connection. The memory 5012 of the computer device 501 (server computer device 501) contains one or more structured data arrays containing at least a linguistic sentence to be converted, and may also contain any of the previously described source data structures for any of the previously described methods structured data array conversion. Moreover, the one or more structured data arrays to be converted may be loadable and stored, in particular, in the database of the structured data array conversion system 503. By way of example, and not limitation, computer readable storage media (memory 5012) may include random access memory (RAM); read only memory (ROM); electrically erasable programmable read-only memory (EEPROM); flash memory or other memory technology; CDROM, digital versatile disk (DVD) or other optical or holographic data carriers; magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, carrier waves or other data carrier that can be used to encode the required information and which can be accessed through the device 501. The memory includes a data carrier based on computer storage device in the form of volatile or non-volatile memory, or a combination thereof. Exemplary hardware devices include solid-state memory, hard disk drives, optical drives, and so on. An approximate environment is stored in the memory, in which the procedure of converting a structured data array can be performed using computer commands or codes stored in the device's memory. The device contains one or more processors 5011, which are designed to execute computer commands or codes stored in the device’s memory in order to ensure the implementation of the procedure for converting a structured data array. Computer commands or codes stored in memory are designed to perform the transformation of a structured array of data. System 500 may also include a database (DB) 503. DB 503 may be, but is not limited to: a hierarchical database, a network database, a relational database, an object database, an object-oriented database, an object-relational database, a spatial database, a combination listed two or more databases, and the like. DB 503 stores data in memory, which can be, but is not limited to, read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, CDROM, digital versatile disk (DVD) or other optical or holographic data carriers; magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, carrier waves or other data carrier that can be used to store the required information, and which can be accessed through a structured data array device 501. DB 503 is used to store data representing at least the commands for performing the steps of the previously described methods for transforming a structured data array; one or more structured datasets to be converted, containing at least a linguistic sentence, or one of the previously described initial data for any method of converting data structures that can be loaded into the memory 5012 of the structured dataset 5012; and other data necessary for the functioning of the system. The exemplary structured data transformation system 500 may further comprise a server computer device 501, which, in addition to the functions described previously, stores and facilitates manipulation of computer commands or codes previously described in this document, which, respectively, are not further described. The server computer device 501, in addition to the functions described earlier, can regulate the exchange of data in the system 500 by converting a structured array of data, and also provides data processing provided one or more than one user computer device 502 is connected to it. In this case, all the computing powers necessary to ensure the implementation of the procedure for converting a structured data array, are located on the server computer device 501. The system 500 can also The network contains one or more data networks 504. The data transfer networks 204 may include, but are not limited to, one or more local area networks (LANs) and / or wide area networks (WANs), or may be an information and telecommunications network, the Internet, or an Intranet, or virtual private network (VPN) , or a combination of them, and the like. The server computing device 501 also has the ability to provide a virtual computing environment (Virtual Machine) to provide interaction between user computing device 502 and DB 503. Network 504 serves to provide interaction between computing device 501, database 503 and user computing device 502 of the structure 500 array of data. In this case, the user computing device 502 may be connected to the server computing device 501 directly using wire and wireless communication methods and methods known from the prior art, which, respectively, are not further described in detail.

Claims (36)

1. A method for converting a structured data file (CIC) executed by a processor of a computer device, containing at least a linguistic sentence characterized by the following steps: A) the formation of the first data structure, which form the first data structure of the MD, containing the elements of the first data structure, said elements of the first data structure being the textual elements (TE) of the linguistic sentence, as well as the identification data of the text elements (identification data of the TE), representing for each TE, at least: the value of the text element (the value of the TE) and the sequence number of the text element (the sequence number of the TE) in the linguistic sentence AI; B) the formation of a database of linguistic features (BDLP), which reveal the linguistic features of the text elements (linguistic signs of TE) of the linguistic sentence, from which form a database that represents the BDLP of text elements of the linguistic sentence; C) forming the second data structure, on which the second data structure of the MDD is formed, containing elements of the said second data structure, said elements of the second data structure being syntactic units (CE) of the linguistic sentence, formed on the basis of information from the BDLP of textual elements of the linguistic sentence, also represent the identification data of syntactic units (the identification data of the CE), representing for each CE at least: the value syntactic unit (CE value) and ordinal (s) number (s) of TE linguistic sentences that make up CE. 2. The method according to p. 1, characterized in that in stage A) perform the method, characterized by the implementation stages: A1) identify the original data structure of the MDD, which identifies the elements of the original data structure of the MDD, which are linguistic sentences; A2) identifying the elements of the first SMD data structure, which identifies the elements of the first SMD data structure, which are the textual elements (TE) of the linguistic sentence, as well as the identification data of the TE, which for each TE, at least: the TE value and the sequence number of the TE, and form the first data structure of the MD. 3. The method according to claim 2, characterized in that within stage A1) provide a classification of the elements that make up the original data structure, as linguistic sentences. 4. The method of claim 2, characterized in that in step A2) identify the elements of the first SMD data structure, which are the textual elements (TE) of the linguistic sentence, by identifying individual words or groups of words, numbers (numbers) or indices, and the numbers (numbers) or indices are not separated by a space, as well as punctuation marks. 5. The method according to claim 4, characterized in that the last punctuation mark in the linguistic sentence is not taken into account during identification and is not considered as a text element of the linguistic sentence. 6. The method according to claim 2, characterized in that in step A2) the identification of the value of the text element is produced by registering the characters (letters, numbers and / or punctuation marks) that make up the text element, and the identification of the sequence number of the text element is produced by calculating the location of the text element in the linguistic sentence. 7. The method according to claim 6, characterized in that the first text element in the linguistic sentence receives a sequence number "1", and all subsequent text elements receive a sequence number greater by one than the sequence number of the previous text element. 8. The method according to p. 1, characterized in that stage B) is characterized by the implementation stages: B1) the formation of linguistic features of textual elements of the linguistic sentence, which for linguistic analysis of the text element provide the identification data of the element (value and ordinal number of the text element) and receive the linguistic characteristics of the text elements of the linguistic sentence, as well as the values of the said linguistic characteristics 2131; B2) forming a database of linguistic features (BDLP), on which BDLP of textual elements of the linguistic sentence are formed; moreover, the linguistic feature of the text element is all the linguistic characteristics obtained for the text element during the execution of step B1) that have values of linguistic characteristics. 9. The method of claim 8, characterized in that within step B1) the linguistic characteristics and their meanings are formed by a comprehensive linguistic analysis of each textual element of the linguistic sentence, representing, by way of example, but not limitation, a comprehensive analysis of the text element based on location text element in the structure of a linguistic sentence, its meaning, type, classification of its mental image and analysis of its connections with other text elements in the linguistic sentence ii, whereupon the formation of basic linguistic characteristics. 10. The method according to claim 8, characterized in that the formation of BDLP is carried out by entering formed in the framework of stage B1) linguistic characteristics and their values in BDLP as a list of the first part of the linguistic characteristics with the values of these characteristics. 11. The method according to claim 1, characterized in that step B) is characterized by the implementation of the steps: B1) identify and form the first elements of the second SMD data structure, which identify and form the first elements of the second SMD data structure, which are the first syntactic units, as well as the identification data of the first syntactic units, which for each first syntactic unit is at least the first syntactic unit and the ordinal (s) number (s) of a text element or textual elements of the linguistic sentence that make up the first syntax th unit; B2) forming the second elements of the second SMD data structure, on which the second elements of the second SMD data structure are formed, which are the second syntactic units, as well as the identification data of the second syntactic units, which for each such syntactic unit are at least the value of the second syntactic unit and the sequence numbers of the textual elements of the linguistic sentence constituting the second syntactic unit; B3) forming the second data structure of the MDD, on which the second data structure of the MDD is formed by combining the first syntactic units, second syntactic units and their identification data. 12. The method according to claim 11, characterized in that in step B1) the identification or formation of the first syntactic units is carried out by a comprehensive analysis of the values of the linguistic characteristics of the text elements of the linguistic sentence, the first syntax units consisting of one text element being identified, and subject to the first syntactic units, consisting of several text elements, while identification or formation is carried out by identifying Ia first syntactical elements with current source syntactic objects representing a list of initial syntactic objects previously established and stored in the first user database. 13. The method according to claim 11, characterized in that, as part of stage B2), the formation of second syntactic units from two or more first syntactic units is carried out by a comprehensive analysis of the values of the linguistic characteristics of the text elements, which are the first syntactic units, while identifying the linguistic characteristics of the text elements, make up the first syntactic units that correspond to the description of the syntactic structure contained in the first user database. 14. The method according to claim 11, characterized in that, within the framework of step B1), the meaning and serial (serial) number (s) of the first syntactic units are identified as follows: the value (s) of the text (text) element (s) of the linguistic sentence constituting (constituting) the first syntactic unit is identified as the value of the element of the first syntactic unit, and the ordinal (ordinal) number (s) of the said (mentioned) text (text) element (s) of the linguistic rule The units constituting (constituting) the first syntactic unit are identified as the ordinal (s) number (s) of the text (text) element (s) 312 constituting (constituting) the first syntactic unit. 15. The method according to claim 11, characterized in that within step B2) the identification of the meaning and sequence numbers of TEs of the second syntactic units is made as follows: the values of the textual elements of the linguistic sentence that constitute the second syntactic unit are identified as the value of the second syntactic unit, and ordinal the numbers of the mentioned textual elements of the linguistic sentence constituting the second syntactic unit are identified as the ordinal numbers of the textual elements constituting the second syntactic unit. 16. The method according to claim 11, characterized in that, as part of step B3), the formation of the second SMD data structure is carried out by combining the first syntactic units and second syntactic units in one data structure. 17. The method according to claim 12, characterized in that within stage B1) the identification of the linguistic characteristics of the TEs that make up the first syntactic units and their meanings, if necessary, is done by organizing a query into the BDLP, formed within the framework of stage B), consisting of the identification data TE, constituting the first syntactic unit, and obtaining the values of the linguistic characteristics of the textual elements of the linguistic sentence of which the first syntactic unit consists. 18. The method according to claim 13, characterized in that in step B2) the identification of the linguistic characteristics of the TEs constituting the second syntactic units and their meanings, if necessary, is carried out by organizing a query into the BDLP, formed within the framework of step B), consisting of the identification data TE, constituting the second syntactic unit, and obtaining the values of the linguistic characteristics of the textual elements of the linguistic sentence, of which the second syntactic unit consists. 19. A computer device for converting a structured data file containing at least a linguistic sentence containing at least: computer device processor and a memory containing program code which, when executed by the processor of the computing device, causes the processor of the computing device to perform the steps of the method according to any one of claims. 1-18. 20. A system for converting a structured data file containing at least a linguistic sentence containing at least: the server computing device, which is the computing device of claim 19, and A user computing device capable of transmitting commands or instructions to the server computer device to cause the processor of the server computer device to execute program code, which, when the processor computer executes the server computer device, causes the processor of the server computer device to perform the method of any one of claims. 1-18. 21. A computer-readable storage medium containing a program code that, when executed by a processor of a computing device, causes the processor of the computing device to perform the steps of the method according to any one of claims. 1-18.

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