NL8901050A - Grammar processor for natural language sentences - by determining each constituents functional category, determining closure step and applying context rules for best representation - Google Patents

Abstract

The grammatical processing is performed by measures applied separately to each word unit of the sentence. The measures applied are as follows:- A. For each word unit and each constituent, its functional word category within the constituent is determined by referring to data concerning the verbal category of the word unit and category of the constituent. B. Finding a step leading to closure of the constituent by reference to data concerning the dominant category of the constituent. C. Testing the current constituent against grammar based rules regarding the context of words/constituents and, if required, assessing the probability factor of the sentence representation.

Description

Océ-Nederland B.V. in Venlo

Method for parsing and correcting a sentence in a natural language, as well as a device for carrying out such a method

The invention relates to a method for parsing and correcting a grammatically incorrect sentence expressed in natural language, wherein the parsing of this sentence in phrases to be described with functional indications takes place on the basis of word units, which according to verbal categories and application -oriented categories have been legalized, as well as an apparatus for carrying out such a method.

A method thus described for parsing a natural language sentence, which method is referred to in professional circles as "parser", is known from: Allen, James; Natural Language Understanding. The Benjamin / Cummings Publishing Company,

Inc., Menlo Park, U.S.A. 1987.

The parsers described there have a so-called "rewriting mechanism", which means that the parsers perform a parsing according to a large number of rewriting rules.

These rewriting rules link a group of words and / or sentence constituents on the one hand, and a parent constituent, that is, a constituent that dominates this group on the other. The number of rewriting rules depends on the size of the description mechanism to be used, which underlies the parser; the descriptive mechanism is in turn determined by the syntax and morphology of the language, which imposes limitations on the parser in terms of its ability to come up with a solution to the sentence in case of a non-grammatical input. Only by including a very extensive range of rewriting rules in the parser is it possible to parse incorrectly formulated, as well as less common sentence constructions. As a result, the memory space of the computer on which the parser runs is intended for the rewrite rules, while the length of time to parse such a sentence may be long. In addition, it will be very difficult to detect non-grammatical expressions. The invention aims at this disadvantage

To be extensively resolved.

The invention is based on the insight to bind the parsing to rules ("right associate grammar rules") in order to fit a word within the existing or newly to be formed constituent in the already obtained phrase representation, while granting a certain functionality at word level. (functional word category) on the basis of at least one verbal category appropriate to that word, and rules ("constituent closure grammar rules") to investigate the possibility of closing a constituent by granting a functionality, whether provisional or not, on constituent level (functional constituent category), during which during the parsing procedure an expected factor for the sentence is maintained on the basis of an investigation into the connection between the various words and / or constituents within the same constituent level, on the basis of which the most obvious sentence representation can be selected. According to the invention, the method of the type described in the preamble is characterized by the following steps to be performed per word unit from the sentence: a. Determining the functional word category per word unit and per constituent within the constituent and / or within a new context. constituent to be created, based on information about the verbal category of the word unit concerned and the category of the constituent; b. Describing for each constituent on the basis of information about the category of the constituent and the category of the constituent dominating this constituent a measure concerning the closure of the constituent, as well as the granting of a functional label, whether or not provisional, to be completed at that time. closing constituent; c. Testing the present constituent against syntax-based rules regarding the coherence of words and / or constituents within this constituent in at least one of the latter two steps, and, if necessary, revaluing an expectation factor assigned to the sentence representation, and selecting any sentence representation whose expectation factor is above a certain threshold; and d. Selecting the grammatically incorrect Constituent within the sentence and then changing this Constituent based on rules based on syntax rules.

The parser to be described in a first embodiment is a parser with an external grammar (syntax directed parser) in which the grammatical rules are kept outside the actual program part, and are stored in memory parts or memory modules. This offers the possibility to change the grammatical content outside the program. Furthermore, by only changing the contents of the memory parts or memory modules, the parser can be made suitable for another natural language. The grammatical rules have such a form that it is possible to process a large number of possible structures with a limited number of rules.

Moreover, this parser will generally still come up with a solution for non-grammatical input and even indicate what kind of error has been made. This makes the parser suitable for use within an editor, for example. The results of the parser as well as the basics of this parser are the starting points of a program to correct incorrect sentences, and also to correct a text with inconsistent word usage or to introduce a different word choice in a text.

In addition to the above-mentioned embodiment of a parser with an external grammar, a parser with an internal or integrated grammar (syntax embedded parser) is of course also possible by accommodating the grammar rules within the parser. This can result in a faster parser.

The invention will be explained in more detail with reference to the annexed figures, of which:

Fig. 1 shows by means of a flow diagram a general overview of the working method to be followed when parsing a text;

Fig. 2 shows a flow chart of the basic principle of the parser;

Fig. 3 shows in a flow diagram a first embodiment of the core portion of the structure shown in FIG. 2 flow diagram shown;

Fig. 4 shows in a flow diagram another embodiment of the system shown in FIG. 3 core section shown;

Fig. 5 shows in a flow diagram yet another embodiment of the system shown in FIG. 3 core section shown;

Fig. 6 shows a detailed flow diagram of a first common portion from the core portion shown in FIGS. 3 to 5;

Fig. 7 shows a detailed flow diagram of a first portion of the structure shown in FIG. 6 common part shown;

Fig. 8 shows a detailed flow diagram of a second portion of the structure shown in FIG. 6 common part shown;

Fig. 9 shows a detailed embodiment of a second common portion from the core portion shown in FIGS. 3 to 5;

Fig. 10 shows a flow diagram of an application-oriented part of the system shown in FIG. 2 flow diagram shown;

Fig. 11 in a flow chart shows a detailed view of part of the structure shown in FIG. 10 flow chart shown;

Fig. 12 in a flow chart shows a modification of a portion of the structure shown in FIG. 7 flow diagram shown;

Fig. 13 depicts a flow chart of a schematic overview of a particular application form of said parser;

Fig. 14 shows a flow chart of an important phase of the process shown in FIG. 13 application shown;

Fig. 15 depicts a flow chart from one to FIG. 14 belonging program part;

Fig. 16 shows a flow chart from another to FIG. 14 belonging program part;

Figs. 17 through 23 show a number of flow diagrams of detailed correction programs of FIG. 16;

Fig. 24 shows a flow chart of a first aid function from the program regarding the particular application of said parser;

Fig. 25 depicts a flow chart of a second auxiliary function from the program with respect to the particular application of said parser;

Fig. 26 shows a flow chart of a first portion of a particular mode of operation of the one shown in FIG. 13 application form shown; and FIG. 27 depicts a flow chart of the flow chart shown in FIG. 26 connecting part.

A parser provides the means to convert a sentence, expressed in a natural language, into a syntactic representation using a formalism, which expresses the relationships between the different entities. That formalism is based on the idea that it is possible to represent the self-contained phrases (constituents) of a sentence through a hierarchical structure, such as a branching network (tree structure).

Strictly speaking, the input of the parser does not comprise a sentence line, but a series of words obtained by lexicalisation of the sentence. As shown in Fig. 1, this means that every sentence presented at program phase 1 must first be lyxized at program phase 2 before the parser parses the sentence at program phase 3. When lexicalizing a sentence, each word is called lexical information related to the possible verbal categories and the application-oriented information of each word by means of a so-called lexical memory, which is part of the computer memory or which is present on a memory disk (disk). categories are searched for and / or generated, and this information is stored by means of one or more word structures in a word memory, which is also part of the computer memory. The results of the lexicalization process of a word unit with respect to the application-oriented categories will be collected below under the term "Features". In the course of the description it will be discussed why there may be more than one word structure, but first the term word structure will be explained in more detail.

A word structure is an assembly of data elements associated with a word, whereby those data elements are assigned a structure with a number of memory fields. The word structure includes the following fields: a Category field, a Command field, a Row field, and a Features field. The Category field contains the word category found in lexical memory, for which the following word indications are eligible, for example: Article ("article"), noun ("noun"), pronoun ("pronoun"), verb (" verb "), preposition (" P-word "), conjunction (" C-word "), adjective (" adjective ") or adverb (" adverb "). This is only an example and depends on the dictionary and grammar tables used.

The Command field is initially empty, but will be filled in later by the parser. The meaning of the Command field will be further explained in the description of another structure, namely the constituent structure, in which such a Command field is also present.

The Row field is filled with a "String" representation of the Word, i.e. a linear arrangement of the elements of the Word. The Attributes field contains the other Word Attributes, i.e. those word attributes, which were obtained during the lexicalization process but which are not included in the Category field. The word attributes included in the Attributes field are of a functional nature.

The above will be explained by means of two examples: At the word “house” in Category field is entered: “noun (noun)” (noun); in the Command field: “NIL”; in the Row -field: "house" and in the Characteristics field: "3rd person singular" (sing 3) and "neuter" (neuter).

As a result of such a representation of a word structure, a word such as "regent" has a Category field with the entry "verb" (verb) as well as a Category field with the entry "noun" (noun) with bij each Category field obtains its own Attributes field.

Since a Word can thus occur in several word categories, and furthermore as a result of ambiguous relations between Constituents, multiple sentence structures between these phrases are conceivable, this approach leads to multiple forms of tree structures, and thus to multiple syntactic representations of the parsed sentence. The parser will always try to include every word structure of the current word within every open constituent structure. This means that the parsing speed decreases when many representations are present.

Since in hindsight not all representations prove to be suitable, it is the object of the invention to investigate in the meantime how, in the interim, that is, during the active phase of the parser, one or more less attractive forms of representation of phrase structures can be eliminated. turn into. The starting point is that after each phase in which a word is added to the existing representation form, the Constituent involved is subjected to certain syntactic rules, and on the basis of certain error detections the initial probability factor, which is assigned the Constituent, according to a system of respective correction factors is lowered, and then the corrected probability factor is tested against a certain threshold value. All forms of representation of Constituents with a probability factor that is less than that threshold can then be eliminated as "less likely". This procedure is then repeated to include the next word within the representation structure.

Such an action can take place immediately after the inclusion of a word in an existing or new constituent, but can also take place after a subsequent investigation into the conclusion of that constituent. With the parser to be described here, such a filtering action will take place in both situations.

Although the lexicalization as described here takes place before the actual decomposition so that the parsing process starts only after all words have been lexicalized, it is also possible to lexicalize one word at a time and then parse that word, lexicalize the next word - if possible in the meantime - and then parsing etc. An advantage of such an approach could be that it is then possible to start parsing a sentence while a user is still typing the sentence (real time parsing).

However, the flow diagram to be described below assumes a lexicalization that precedes the actual parsing process. The parser is then called after lexicalisation. If it succeeds (Y) in finding an analysis in step 4, this analysis can be used in the rest of the program (step 5). This can be a tree drawing program, in which a graphical representation of the found decomposition is drawn, an editor, an indexing and retrieval system, etc., after which the next sentence can be continued in step 1. However, step 4 does not lead to a usable result (N), the parser failed to find a good analysis. This will mean that the sentence was very ungrammatical. For this purpose, an action to be further described may be taken, after which the next sentence in step 1 can be continued. Before starting with the actual description of the parser (see step 3), it is important to add another structure, namely to describe the Constituent structure. The Constituent Structure is a phrase-related assembly of data elements, which includes the following memory fields: Category field, Category field, Command field, Members field, Features field, Stack field, Error field (Violations field) and a Probability field.

The Category field is reserved for information about the category of the constituent, which in our example grammar should include the following phrases: main, sub- or clause (Sentence with the abbreviation S), the nominal phrase or phrase (nounphrase with the abbreviation NP), the preposition group or phrase (Prepositional phrase with the abbreviation PP) and the adjective / adverbial phrase (adjective / adverbial phrase with the abbreviation AP). The Category field initially contains the designation NIL, but will be filled in with the information about the constituent during the parsing process. The Command field is the field that contains, after parsing, address information (pointer) about the Parent constituent, i.e., the Constituent which dominates the present constituent.

The Structural Elements field is reserved for information about one or more pairs of the functional label that occur in pairs with a Word or Constituent structure belonging to this constituent, as well as the address information about the relevant Word or Constituent structure. In general, a Constituent can be composed of a number of Word structures and / or Constituent structures.

The functional labels used here in the sample grammar include the following: - Subj: Subject (Subject) - Indobj: Contributing Object (Indirect Object) - Obj: Direct Object (Object) - Smod: Sentence Modification (Sentence Modification) also known as a "further adverbial provision" (Adverbial

Modification) - Comp: Complement - Pred: Predicate (Predicate) - fNP: functional NP, to be used as a provisional label, which will later be replaced by a definitive functional label at sentence level - Nmod-a: a modifying provision for an independent

(used) noun in the form of an AP

- Nmod-s: a modifying provision for a self-employed person

(used) noun in the form of an S

- Nmod-p: a modifying provision for a self-employed person

(used) noun in the form of a PP

- Det: a determining pronoun or article (determiner)

- Head: central element within an NP, PP or AP

- Pobj: a section, connecting to a preposition

sated by a POI

- Amod: a modification of the main word of an AP

- Seq: a connecting word incl. Comma sign, with juxtaposition between two phrases or sentences (sequencer) - Conj: one of the subordinate phrases.

The Characteristics field is reserved for the information about the characteristics belonging to the Constituent. As soon as a Constituent is created with a certain Category, the Attribute field will be filled with the attributes belonging to the Category. It should be noted that, in the case of a Word Category, the Attributes field is provided with the attributes associated with that Word found during the lexialization process. During the parsing process, for each element (word or Constituent) that must be included in the relevant Constituent, the Characteristic field of the relevant Constituent will be adapted to the information associated with that element. The Stacking Field contains a list of the functional labels, which are also listed in the Structural Elements field of the Constituent. The Error Reporting Field contains information about all error codes related to incorrect grammaticality made within the Constituent. This field is initially empty.

The Probability Calibration Field indicates the probability calibration factor attributed to the occurrence of this Constituent. Initially, this will be "1", but for every incorrect grammaticality detected, this value will decrease by a value depending on the type of such incorrect grammar detected.

With the help of the Constituents it is possible to compose a parser tree. After all, every Constituent can in turn contain Constituents and / or Words. In addition to the functional category, the Structural Element field also indicates the memory address information associated with the Constituent or Word structures. On the basis of this information it is possible to descend into the parsing tree. Conversely, the Command field of a Constituent provides address information about its Parent constituent, i.e. the other Constituent dominating Constituent, which provides the opportunity to get higher in the parsing tree. It is noted that Words cannot contain structural elements, while the Command field of the highest Constituent (root) in the parsing tree contains no information (NIL).

The parser, as can already be seen to some extent from the Probability Calibration Field, works with probability calibration factors and has a threshold value that can be modified if necessary, against which all available structures are tested for their calibration factor, and where only structures with a probability! calibration factor, which is greater than or equal to the threshold value, are processed by the parser. This makes it possible to perform the parsing of grammatical and near-grammatical sentences more quickly.

In the following section, the operation of the parser will be explained in more detail, it is important to note here that the parser is based on the understanding that a Word of a certain Category within a Constituent of a certain Category often occurs will have a clearly defined functional meaning within the Constituent. The same goes for Constituents within Constituents. The parsing method is therefore based on the fact that it will usually be sufficient to know the Categories of the Parent Constituent on the one hand, and those of the Word or Constituent on the other in order to know the function (functional category) of that Word or Constituent within determine the Parent Constituent.

A program associated with the parser is shown in the following figures by means of a flow diagram, according to which the method of parsing a text in a computer is carried out.

The entire parser will first be described in a fairly global manner. Two program parts, the so-called "fitting a word in an existing or new Constituent" ("word right associate") and the "closing a Constituent" ("closure") will only be indicated briefly, after which In a subsequent part of the description, these program parts are explained in more detail with reference to detailed figures.

The method to be described can be divided into two phases, in which in the first phase, which in fact comprises the actual parsing process, the possible sentence representations are formed by means of a syntactic analysis, and in the second (additional) phase definitive functional labels on constituents with still have an unclear functional character. Appropriate filtering procedures will be discussed in both phases.

This method is carried out word by word (with all its functions of use) and will be carried out again whenever a next word is to be included in the representation structure.

In the flow diagram of Fig. 1 commences the reading phase of a sentence in order to be able to carry out the parser's method with reference numeral 1. In this phase, the sentence to be parsed is presented to the computer in a known manner (for example by means of a keyboard), and the sentence word for word written in a memory part to be designated as word memory in the computer, wherein the number of words (kmax) of which the sentence is composed is also calculated. The guideline here is that the words are separated by spaces, tabulations and punctuation marks, and that each punctuation mark is included in a word category. The stated number of kmax is also kept in the word memory.

Then the next phase (2), the lexical description of all words from the offered sentence, takes place. The word structures present per word are searched for in the words of the sentence offered, which is done on the basis of a memory part, which is to be designated as lexical memory, which is present in the computer memory, and in which a large collection with one or more word structures possibly occurring is stored.

A detailed explanation of phase 2 will be illustrated with reference to FIG. 2 occur. The lexical description takes place there. In the next program step 6, a counting unit (k-counter), which indicates the rank number of the word to be treated (k), is reset to 0.

Then, in step 7, the count of the k-counter is increased by 1 (k = k + 1), after which in step 8 it is examined whether the count of the k-counter has already exceeded the maximum k-value (kmax) (k> kmax). If this is the case (Y), the program proceeds to step 11, if not (N), the program proceeds to step 9, in which the next word from the word memory means a by the counting position of the k- counter determined address is retrieved and written to a memory section to be designated as working memory in the computer. Furthermore, in step 10, the word written in the working memory is retrieved in the lexical memory and the specific information occurring there is added to the word in the word memory.

Then the program returns to step 7. Since in parsing each word must be examined for all listed word functions (word categories), each word with a deviating word category and / or other deviating characteristics will have its own rank number (1) in the corresponding Word structure , while the number of assigned rank numbers (lroax, k) per word 00 will also be kept. Instead of Omax, k) it is also sufficient to assign a specific label to the last array in order to indicate in the following syntactic analysis that the last word function of that word has been reached.

During the syntactic analysis to be carried out in phase 3, multiple representations with respective constituent structures may simultaneously appear as possible solutions, which have different probability factors due to conflict with certain grammar rules. Since one is only interested in the solution or series of solutions with the highest probability factor, solutions with a lower probability factor should be classified as an uninteresting solution and should therefore be eliminated. This is done by testing the probability factors associated with these solutions on the basis of a certain threshold value. This threshold value is set to the value "1" at the start of the syntactic analysis, but can be adjusted to a lower value during that analysis, if it appears that none of the probability factors obtained meet the threshold value. Accordingly, the program includes a step 11, wherein the initial threshold value is set to "1".

Then, at step 12, an initial constituent for the sentence is made. This is a Constituent, the initial stages of which include the following information:

Category field: S

Command field: NIL

Structural element field: NIL Characteristic field: NIL

Stacking field: NIL

Error message field: NIL

Probability field: 1

In order to fill in the Characteristics field, a memory section to be designated as the first tabular memory (see table A) looks at the Characteristics indicated under category S. Since no Characteristics are indicated in this preprogramme, the associated field remains empty (NIL). The memory also comprises a so-called Representation memory for recording current Constituents (for example in list form as is usual with the programming language LISP), with which the parser will always work. In this Representation Memory, which has hitherto been empty, the initial constituent S is written.

Then, at step 13, the k-counter is reset to the initial value "0", and at step 14, the count of the k-counter is increased by "1". After step 14, the program arrives at step 15, which examines whether all words (including the punctuation marks) in the sentence have already been involved in the syntactic analysis and whether the count of the k-counter therefore applies: k> kmax . If this is the case (Y) then apparently every Word is included in the Constituents and the syntactic analysis should be considered as completed.

If in step 15 the statement k> kmax is not true (N), the program proceeds to step 16. The fitting of the word indicated with the aid of the k-counter in the Constituent structures available at that time will commence, namely in the as yet unfinished Constituent structures, which are located in the aforementioned representation memory.

All Word structures of this word are now available as a result of the lexicalization process. When fitting a Word with a certain word structure within a Constituent with a certain Category, the Word will in many cases fulfill a certain function, and thus a certain functional Word Category can be assigned. The same will also apply to Constituents within their Parent Constituent at a Tater stage. On the basis of the Constituent Category on the one hand and the Word Category on the other hand, the function (functional Category) of the Word within the Constituent will be determined. If the described incorporation of the Word into the aforementioned Constituent is not directly possible, it is sometimes possible that a new Constituent can be linked to it, within which the rapture of the Word is possible. It should also be noted that the inclusion of a Word structure in an open Constituent structure on the basis of a number of grammar rules and because of the number of Word structures (lmaXj | ς) in that Word (k) can yield a certain multiplication of the number of Constituent structures. Since the results of the parsing process will always be included in the Representation memory, and the current Constituent structures occurring therein must be taken as input values for the parsing process, in step 17 a memory part of the computer, to be designated as "Temporary Memory", is first empty, the Representation Memory with all its Constituent Structures is then transferred to the Temporary Memory in step 18, and then the Representation Memory is empty in step 19. Several variants of the following program section 20 are possible. These will be explained successively with reference to Figures 3, 4 and 5.

Assuming that with a Word (k) with several Word structures (1) the connection possibility must be checked for each structure, the computer comprises a counting unit (so-called 1-counter), the counting position of which corresponds each time to the relevant word structure.

For a next word (k + 1), which must be included in the existing phrase structure (Sm), the 1-teiler must also be reset to 0, which is also the case with the counting unit (so-called m-counter) , which represents the rank numbers (m) of the constituents.

Accordingly, at step 21 in FIG. 3 the count of the 1-counter is reset to 0 (1 = 0), after which in step 22 the count of the 1-counter is increased by "1" (1 = 1 + 1).

In step 23, the question is asked whether the count of the 1-boiler has already exceeded the maximum value (lmaXj k ^> which represents the number of Word structures of the word with rank number k (l ^ max)

If the question is answered positively (Y), the program proceeds to step 24.

However, if the question in step 23 is answered in a negative sense (N), then in the next step 25 the 1st Word structure will be brought from the Word memory to the Working memory to transfer the previous Word structure, in order to transfer to the newly registered Word structure perform a number of operations. Then, in step 26, the m-counter will be reset to 0 (m = 0), and then in step 27, the count of the m-counter is increased by "1" (m = m + l). Then, in step 28 the question arises whether the count of the m-counter has exceeded the number ι% 3Χ, which represents the number of constituents then occurring (m> mmax) .If this is the case (Y), then it has been established that the word (k) to be fitted with the conscious structure (1) after connection has been examined in all Constituent Structures currently present in the Temporary Memory, and that therefore this program part should be repeated with the same word (k) but then for a next Word structure (1 + 1) Accordingly, the program jumps back, and returns to step 22. In case of a negative answer (N) to the question in step 28, step 29 follows, where the mth Constituent from the Temporary Memory is retrieved and sent to working memory for oversc friction of the previous Constituent is brought. Thus, both the 1-th Word structure of the k-th Word and the m-th Constituent are in the Working Memory. With these two structures (Word structure and Constituent structure) a number of operations are performed in the program section 30.

In fact, an attempt is then made to place the Word structure within the Constituent structure, possibly by creating other Constituent structures. The program section is further shown in FIG. 6 elaborated. After execution of the program section 30, the program returns to step 27.

If in step 28 the question is answered in the affirmative (Y), the program returns to step 22. This means that the process is to fit a word right (word right associate-process) for one word structure (1) at one word (k ) performed on all current constituents (ι% 3Χ).

At some point after the question is answered in the affirmative at step 23 (Y), the program proceeds to step 24. At that point, the process of "inserting a word to the right" for all word categories (l „, ax) is a word (k) is performed on all current constituents (ι% 3Χ), and the constituents thus formed are stored in the Representation memory. All these constituents now need to be subjected to a "closing constituents" program section. To this end, the Temporary Memory will first be emptied at step 24, and at the next step 31 all constituents stored in the Representation Memory will be transferred to the Temporary Memory. Then, at Step 32, the Representation Memory is cleared. In the subsequent step 33, an m * -te! 1er, the count of which corresponds to a certain constituent in the Temporary Memory, is reset to 0 (m * = 0). In the next step 34, the count position of the m * -teil er is increased by "1" (m * = m * + l). Then, in step 35, the question is asked whether the m * counter has already exceeded the maximum value (m * max) corresponding to the number of constituents (πτ ^ πι ^ χ). If this question is answered in the affirmative (Y), then all representations (m * max) obtained in all word categories (lmax) of the kth word have been subject to the program section for "closing constituents". The program then returns to step 14 to make representations using the next word (k + 1).

If, however, the question is answered in the negative in step 35 (N), then in the next step 36 the m * -th representation is taken from the Contemporary Memory and then in step 37 to the previously mentioned program section for "closing constituents". "subject. The result obtained during this step is hereby written into the Representation memory, after which the program returns to step 34.

At step 15 in FIG. 2 the question is answered in the affirmative (Y), then all words (kmax) with all associated Word structures (lmax, k) 1n are placed in the constituents, and in the next step 38 the question is asked whether at least one Constituent exists in the Representation Memory. the Command field is empty. After all, an empty Command field indicates that we are dealing with the upper Constituent or Top constituent (Root). This question is real, because in steps 30 and 37 a filtering procedure has been built in, which filters out (eliminates) faulty representations, and this by means of a threshold circuit in which the value of the Probability field is compared with the current threshold value. This comparative study will be further explained in Figures 6 to 9.

If there is a negative answer (N) to the question in step 38, it must be ascertained whether the program section thus described about the parser will yield a useful result, i.e. a meaningful representation, at a lower threshold value. However, the threshold value may not be lowered below a certain value, for example 0.2, since it is then considered that the sentence presented is structurally and grammatically wrong in such a way that no useful representation from the parsing process should be expected. Accordingly, if the question is answered negatively (N) at step 38 during the next step 39, the question will be asked whether the threshold value is still above a predetermined minimum value, for example 0.2. In the affirmative answer (Y), in the next step 40, the threshold value will be set to a next lower number value according to a fixed series of number values. The program will then return to step 12 to rerun the program with regard to parsing the sentence presented, but at a lower threshold value. This also allows grammatically incorrect sentences. If the question in question 39 is answered in the negative (N), and therefore it must be assumed that no useful analysis can be found, then a corresponding action will have to be taken. The sentence can possibly be classified as suspicious, with presumably many and / or very serious grammatical errors. If necessary, a notification can also be made. It is allowed to let step 40 precede step 39, wherein step 39 then takes another value as a criterion. In the affirmative answer (Y) to the question of step 38, and thus in the presence of at least one representation of the Summit constituent, in the next step 42 the structural element fields of the Summit constituents present are adjusted. This is based on the situation that the structure associated with the sentence has already been created. However, a number of Command Fields have yet to be completed or modified. The Constituents (Parent Constituents) occurring in the Representation Memory will contain a number of Constituents (Member Constituents) and / or Words (Member Words) in their structural element field. A member constituent is a constituent dominated by its parent constituent. The Mission field of these Member constituents and Member words is now filled with an indication or reference to the relevant Parent constituent. In this way, the Command fields of all Member constituents and Member words, which are mentioned in the Structural Element of a certain Parent constituent, are also provided with an indication or reference concerning this Parent constituent. The same also happens for every Command field of the Constituents and the Words within a Constituent, of which the Command field has been completed during the parsing process.

Since temporary functional labels may have been assigned during the parsing process, they are replaced in step 43 by permanent ones. In the example grammar to be described, the provisional label fNP is used for each Constituent with the Category NP within, among others, a Constituent with Category S. During this step such labels are replaced by the final labels "Subject", "Suffering Object" (Object), "Contributing Object" (Indobj.) And "Predicate" (Pred). This step 43 will be further explained at a later stage. Finally, at Step 44, that Representation having the highest probability calibration factor is selected from the Representation Memory. This can also result in several

Representations. For example, in the sentence "I saw a girl with the binoculars." two solutions are possible, since the phrase "with the binoculars" can be a more detailed definition of the "verb" as well as of the "Suffering Object".

A second embodiment of the program part te 20 will now also be described with reference to Figs. 3 are explained. In addition, the index 1 now refers to a certain constituent structure (and not to a certain Word structure), while thereby the index m refers to a certain word structure. As a running index at steps 33 to 37, 1 * resp. l * max can be used instead of m * and m * max. Accordingly, at step 21, the count of the 1 counter is reset to "0" (1 = 0) with respect to the rank number of the constituent to be used, at step 22, the count of the 1 counter with "1" "are increased (1 = 1 +1), and in step 23 the question will be asked whether the count of the 1-boiler has already exceeded the maximum value (lmax), corresponding to the number of constituents present (1> lmax In step 25, the constituent indicated by the count of the 1-count 1 er is retrieved from the Temporary Memory, which constituent will overwrite the previous Constituent in the Working memory. Furthermore, at step 26, the m-counter, the count of which corresponds to the rank number of a certain Word category, is reset to 0 (m = 0). In step 27 the count position of the m counter is increased by "1" (m = m + 1) and in step 28 the question is asked whether the count position of the m counter corresponds to the maximum value ι%, χ, with the number of word structures, has already exceeded (m> mmax). At step 29, the mth Word is retrieved from the Word memory and the mth Word will overwrite the previous word in the working memory. The m-th Word and the 1-th Constituent are then subjected to the adjustment process of step 30.

An affirmative answer (Y) to the question at step 28 implies that all word structures (ι% 3Χ) at one word (k) after connection to one Constituent (1) in the program section 20 have been examined. The other steps proceed as described above.

In the embodiments already described, all possible representations of constituents are first created or expanded, which are possible with one word (k) for all word structures on the basis of available constituents, before the program part 37 for "closing these constituents" is executed.

In the following embodiment, all possible representations (m * max) of constituents are first created or expanded, which for one Word (k) for one Word structure (T) may be based on all constituents (% ax), before the program section 37 for closing these constituents (m *) is executed. Then the same part of the program is repeated, but for a subsequent Word structure (1 + 1).

The third embodiment based on this train of thought is shown in FIG. 4 is shown.

In step 21 the 1-grower concerning the rank number of a Word structure at Word (k) is reset to "0" (1 = 0), and in step 22 the count of the 1-boiler is increased by "1" (1 = 1 +1). Then, in step 23, the question is asked whether the count of the 1-counter has already exceeded the maximum value Umax) (1> 1max). In step 25, the word with the Word structure defined by the 1-counter is taken from the Word memory and placed in the Working memory. Then, in step 26, the m-counter whose count represents the rank number of a constituent in the Temporary Memory is reset to "0" (m = 0), and in step 27, the count of the m-counter is reset by "1" increased (m - m + 1) In step 28 the question is asked whether all constituents (% ax) have already been examined for connection by the program part of step 30 (m> fflmax} · If the question is answered negatively (N), then in step 29 the constituent defined by the count of the m-counter is taken out of the temporal Memory and placed in the Working Memory, after which in step 30 the connection of the 1-th Word structure to the m-th Constituent structure is examined, and its result is written into Representation memory.

In the affirmative answer to the question in step 28, in the next step 45, the contents of the Representation memory and those of the passive Switch memory are exchanged, after which in step 32 the Representation memory is cleared. Then, at step 33, the m * tener, whose count represents the rank number of a particular Constituent in the Temporary Switch memory, is reset to "0" (m * = 0). In step 34 the count position of the m * counter is increased by "1" (m * = m * + 1), and in step 35 the question is asked whether the count position of the m * counter already has the maximum value exceeded (m *> m * max). If this is not the case (N), the constituent indicated by the m * counter is removed from the Temporary Switch memory at step 36 and subjected to the Constituent exit program part at step 37. The result is then stored in the Represents memory, and the program goes back to step 34. If the question is answered affirmatively (Y) in step 35, in the next step 47 the contents of the Representation memory are copied to a buffer memory and step 48 the Representation memory is cleared.

The program then goes back to step 22. The program part thus executed is then repeated, but then for the next Word structure (1 + 1) at the kth word.

If the question in question 23 is answered in the affirmative (Y), the program goes to step 46, in which the buffer memory is copied to the Representation memory and then the buffer memory is emptied. The program then goes back to step 14 (see Fig. 2).

Instead of placing the result of the process steps 37 and 30 first in the Representative memory and then in the Buffer memory, it is also possible to place the result directly in the Buffer memory. However, this will have the necessary consequences when dealing with these program parts in Fig. 6 and 9.

A fourth embodiment, which similarly differs from the above embodiment as the second embodiment from the first embodiment, will now be described in more detail. The indices 1 and m refer to a rank number with respect to a Constituent and a Word, respectively. The indication 1 * will be used as the running index in steps 33 to 37.

Accordingly, at step 21, the count of the 1-counter with reference to the Constituent to be used is reset to "0", (1 = 0), at step 22, the count of the 1-counter is increased by "1" (1 = 1 +1), and in step 23 the question will be asked whether the count of the 1-count Irish has already exceeded the maximum value (lmax), corresponding to the number of constituents present (1> linax) At step 25, the Constituent indicated by the count of the 1-te er is retrieved from the Temporary Memory and placed in the Working Memory. Furthermore, at step 26, the m-counter, the count of which corresponds to the rank number of a certain Word structure, is reset to "0" (m = 0). In step 27 the counter position of the m counter is increased by "1" (m = m + 1} and in step 28 the question is answered whether the counter position of the m counter has the maximum value ι% 3Χ, corresponding to the number of word structures, has already exceeded (m> i% iax).

At step 29, the mth word structure is retrieved from the Word memory and placed in the Working memory. This m-th Word structure and the 1-th Constituent are then subjected to the incorporation process of step 30, the result being stored in Representation memory, and the program returning to step 27. Thus, an affirmative answer (Y) to the question keeps track step 28, that all Word structures (% ax) at one word (k) after connection to one constituent (1) in the program section 30 have been examined; then, at step 45, the contents of the Representation Memory are transferred to the Temporary Switch memory, and the Representation Memory is cleared. Subsequently, a phase begins at step 33, which leads to the closing process of the Constituents present at step 37. If the question is answered in the affirmative at step 35 (Y), the program proceeds to step 47, after which the program part thus described is repeated, but then for the next Constituent (1 + 1) in the Temporary Memory. If the question in question 23 is answered in the affirmative (Y), the program returns via step 46 to step 14 (see Fig. 2).

In FIG. 5 shows a fifth embodiment of the program part 20, which is based on the idea that each time after one Word and one Constituent have been transferred to the Working Memory, both the program part 30 regarding the fitting of that Word to that Constituent, as well as immediately after the program part 37 to take place regarding the closing of the obtained Constituents. Accordingly, at step 21, the 1-counter, whose count represents the rank of the Word structure, is reset to "0" (1 = 0), at step 22, the count of the 1-counter is increased by "1" (1 = 1 +1), and in step 23 the question is asked whether the count with the 1-teil has already exceeded the maximum value Omax), which corresponds to the number of Word structures at the kth word. If this is not the case (N), then in step 25 the 1-th Word indicated by the 1-counter is taken from the Word memory and written into the Working memory. Then, in step 26, the m-counter, whose count position corresponds to the rank number of the constituent in the Temporary Memory, is reset to "0" (m = 0), and in the next step 27 the count position of m- counter increased by 'T' (m = m + 1). At step 28, the question is asked whether the count of the m-counter has already exceeded the maximum value (% ax) »corresponding to the number of constituents in the Temporary Memory (m> mmax). If this is not the case (N), in the next step 29 the mth Constituent is written from the Temporary Memory to the Working Memory. Then, the program portion 30 regarding the connection of the 1 st Word structure to the m th Constituent structure is executed and included in the Representation Memory. Immediately thereafter, the replenished (or new) constituent (s) is retrieved from Representation Memory and removed and then subjected to the program portion 37 regarding its termination. During step 37, the result is written into Representation memory, after which the program returns to step 27.

If the question of step 28 is answered in the affirmative (Y), the program returns to step 22.

If in step 23 the question is answered in the affirmative (Y), the program returns to step 14 (see Fig. 2).

In a sixth embodiment, indices 1 and m are swapped compared to those in the fifth embodiment.

Therefore, steps 21, 22, 23 and 25 relate to the Constituent representation with index 1 and steps 26, 27, 28 and 29 to the Word structure with index m.

Using the flow diagram of Fig. 6, the program section will now be explained in too much detail.

By means of this program part an attempt is made to place the offered Word structure in the offered Constituent Structure. Although a punctuation such as the "comma" and the conjunctions "and", "as well as" and "or" are considered as Words, and as such are also stored in lexicological memory, they still occupy a separate position with respect to other Words in the parsing process; they can be treated as a Member element within a new Parent Constituent to be created of the respective Constituent, within which the process of fitting those conjunctions or punctuation should actually take place. For this reason, such conjunctions and said punctuation will follow a different path within the word fitting process. Hence, at the beginning of this program section at step 50, the question is asked whether the Word category of the Word presented and to be fitted is indicated in the lexical memory with "Seq". If this is the case (Y), the program goes to step 51. If this is not the case (N), then in the next step 52 the Word structure as well as the Constituent structure, within which the Word is fitted, is written to the Working memory. Then, at step 53, on the basis of the information about the Category field of the Word and that of the offered Constituent, a search is carried out in a memory section to be designated as second tabular memory on grammar rules. For example, in the example grammar indicated, the word category "article" and the constituent "NP" offered belong to the grammar rule "article (NP (det))", which means that the word is incorporated into the offered word by means of the functional label "det". Constituent. Several grammar rules of this type can be found in attached table B.

The next step 54 asks whether the requested grammar rule exists and therefore has a data field. If the data field is empty (Y), and the grammar line therefore does not provide a functional Word label, then the program section 30 regarding the connection of a Word within a Constituent is considered to be finished. This is the case, for example, when the connection of a verb (verb) in an NP needs to be investigated; after all, this does not offer a solution (label! narrow = 0). In the negative answer (N) at step 54, the next step 55 asks whether the grammar line has a data field with only one functional label. If this is the case (Y), as with the line "article (NP (det))", then in the next program section 56 the word presented, in this case "article", with the functional label, in this case "det", incorporated within the current Constituent structure. This program section will be explained in more detail with reference to FIG. 7 are explained. However, if a negative answer is given in step 55 (N) and thus multiple elements occur in the data field, as is the case with the grammar rule "article (PP (det NP))", then in the next step 57 last element in this case NP created a new Constituent, which is inserted between the Parent constituent PP and the Word "article".

This new Constituent thus has the following structure: Category field: the last element of the grammar rule in this case NP. Mission field: Parent constituent in this case PP.

Structural Element Field: NIL, that is, the field contains no information.

Characteristic field: All the characteristics belonging to this Constituent Category (NP), which can be derived from the first tabular memory. In this case: "neuter, inneuter, sing 1, sing 2, sing 3, plu 1, plu 2, plu 3, definite, indefinite". Several examples of this type are included in Table A.

Stacking field: NIL, ie the field contains no information. Error message field: NIL, that is, the field contains no information.

Probability field: 1.

This new constituent structure is now considered to be the current constituent structure.

In the next step 58, the last element i.c. NP is removed from the grammar line, and the program returns to step 55.

Since in the present case only one element remains in the grammar line, the program will now proceed to step 56. Step 56 is performed with the current word structure and the current constituent structure. It should be noted that what is considered to be the current Constituent structure may have been changed at step 57.

At step 51, the offered Constituent (within which steps of 25 to 30 should fit a Word) is copied. In the next step 59 it is checked whether the copied Constituent already has an element "Conj" within the Stack field of the Constituent. If this is the case (Y), it is not advisable to enter a new Constituent again with the prefix "Conj" as Parent Constituent for the copied Constituent and the Word or Punctuation to be inserted. The process then proceeds to step 60, where the copied Constituent is placed in Representation Memory pending subsequent steps 61 to 66, which will involve this Constituent. If the question is answered in the negative (N) at step 59, then step 67 follows, where it is checked whether this Constituent currently already fulfills the conditions for closing a Constituent. A first condition is that the last element added to the Stacking Field is also a suitable element on which the Constituent may end. A second condition is that certain elements must at least be present in the Stack field of the Constituent.

The first condition can also be replaced by another condition, which indicates on which elements a Constituent may not end.

The first, replacement condition and the second condition are examined by means of grammar rules, which are stored in a memory section to be designated as third tabular memory. For example, the information (NP (det Nmod-a) head) indicates that in a NP the last element may not be a "determiner" or "Nmod-a", and that there must in any case be a "head". Several examples are included in Table C. If such conditions are not met by a POI, the value of the Probability field is decreased, and an appropriate error code is included in the Error Reporting field. If these conditions are met, no further action takes place at this step. By lowering the probability factor, it is likely that this constituent will be eliminated in a subsequent filtering procedure (in program section 69).

Also, at step 67, it is examined whether an essential element is missing within the current Constituent. This is done on the basis of a table K, in which a number of group-related combinations of regulations, composed of 3 list segments, are presented per Consituent. This table prescribes that if none of the elements from the first list segment acting as Attributes is present in the Consituent, the members of the second list segment are required and the members of the third list segment are prohibited. For example, the requirement NP ((plu 3 proper pro) (det) O) indicates that if in an NP constituent none of the elements in the first list segment "plu 3", "clean", "pro" is present, the element from the second list segment, ic "determiner" must be present. The third list segment is empty here, and therefore does not impose any obligation. Several examples are included in Table K. If such conditions are not met, the value of the Probability field is decreased, and a corresponding error code is included in the error message field, including the deliberate combination of 1 list segments.

In the next step 68, in connection with the inclusion of a "comma" or the subordinate conjunctions next to the copied Constituent, a new Parent Constituent is also generated, which gets the same Category designation as the copied Constituent, but with the prefix "Conj" added. The Command field of the new Constituent becomes identical to that of the copied Constituent. The remaining fields are completed in the same manner as was the case in step 57.

In the next step 69, a proposal is made to fit the copied constituent within the newly formed constituent with the functional label "Conj". This is done using the functional label "Conj", the copied Constituent structure itself and the newly created Parent constituent. The associated program portion will be explained in more detail using steps 81 to 89, and may lead to the addition of a new Constituent structure to the Representation Memory.

In the next step 70 it is checked whether a Constituent structure has indeed been added to the Representation memory. If not (N), and therefore the copy constituent is eliminated, the sequencer insertion process is considered terminated. If, on the other hand, the question is answered affirmatively at step 70, then step 61 follows, in which the last added constituent is read from the Representation memory and moreover is removed from it. The next step 62 follows an identical program as that which took place in step 56, however, in the stack field the functional label "seq" is represented. Since an element may have been added to the Representation memory at step 62, the question is asked at step 63 whether this is indeed the case. In the case of a negative answer (N), this program part is considered to have ended. In the affirmative answer (Y), the last added element is extracted from the Representation memory in step 64 and a new Constituent structure is then created in step 65 in a manner already described in step 57. The assignment field is filled in with a reference to the Parent constituent. As the Parent Constituent, the Constituent retrieved from Representation Memory in step 64 is now considered to be the current Constituent.

The category field gets the same value as the category field of the member constituent that has the functional label "conj" within the current constituent.

The other fields are filled in as was the case in step 57.

In the next step 66, the newly created new constituent structure is added to the Representation Memory, after which the word fit program within a constituent is considered terminated.

Fig. 7 depicts a flow chart of a detailed program referenced during program sections 56 and 62.

At step 71, a copy of the current Constituent Structure, that is, the structure of the constituent, contains the relevant

Word must be lodged, written in working memory.

At the next step 72, the Functional Label, which at steps 53 and 56, resp. 62 is obtained, added. Then, in step 73, a combination of structural elements, namely the functional label and the Word structure to be fitted, is added as a label pair to the Structural element field. In practice, the address of the Word Structure will be added instead of the Word Structure itself.

Then, in step 74, in a memory section to be designated as the fourth tabular memory, the corresponding set of features is selected for the category of the current Constituent and the functional label of the Word. Any element from this series of Attributes, which does not appear on the Attributes field of the Word Structure, and which does occur on the Attributes field of Constituent Structure, is removed from the Attributes field of the Constituent Structure.

To illustrate what has been mentioned above, the following example is given: for "NP" and "determiner" according to the fourth tabular memory (see table D) the series of characteristics belongs: "neuter, inneuter, sing 1, sing 2, sing 3 , plu 1, plu 2, plu 3, definite, indefinite ". Suppose that the Constituent structure with category "NP" has the characteristics sing 1, sing 2, sing 3, plu 1, plu 2, plu 3, neuter, inneuter, definite, indefinite "Since now the Word structure in the Characteristics field for example has the characteristics" neuter, definite, sing 3 "(as is the case for the article" het "), the attributes sing 1, sing 2, plu 1, plu 2, plu 3, indefinite and inuter must be removed from the Characteristic field of the Constituent structure. In the next step 75, if desired, some control e-operations are carried out, which is done on the basis of a memory part to be designated as fifth table memory (see table E), whereby incorrect combinations are looked at for each constituent type (constituent category). , incorrect order and incorrect number of functional labels in the Stapelveld For example, it is possible in a constituent NP of two functional labels "head" to be interpreted consecutively as an incorrect combination, the functional labels "Nmod-S" and d then a "head" as a combination with an incorrect order, and more than one functional label "determiner" in a POI as an incorrect number of functional labels for such a constituent. Furthermore, an incorrect order of two functional labels is present when a "head" is followed by an "Nmod-A". It must be taken into account here that in the Constituent Structures the last added elements are placed at the front.

Table E indicates these checks with: “NP ((head head)) ((head Nmod-S) (Nmod-a head)) ((det 1))”.

This table can be extended for other constituents and also in the number of test lines per constituent. During this check, both a specific error code and the relevant element pairs are written in the Error message field. A second check is made for each constituent category by detecting incorrect combinations in the feature field using Table F, which is stored as such in a memory section designated as sixth tabular memory. In a NP, for example, the combination "inneuter" and "neuter" associated with the word combination "de huis" can be regarded as incorrect. This is reflected in the absence of both neuter and neuter in the Characteristics field. When the program determines that none of the Attribute combination (neuter, inuter) is present in the Attribute field, an error message and the corresponding attribute combination are included in the Error message field.

It is also possible to look at combinations deemed necessary in the Characteristics field.

Each constituent must display at least one sanctioned combination of Feature labels in the feature field.

For example, the Characteristic field of the NP constituent "a big house" includes the combination "indefinite, sing 3, adj-not-infl., Adj. Enumerative, neuter" while a proven standard combination is for example (indefinite, adj.-not-inflected , neuter), which is found in the said Attribute field. The NP constituent "the big house" has the Characteristics field (definite, sing 3, adj.-inflected, adj. Enumerative, neuter), in which the standard combination (definite, adj.-inflected) is found. Thus, for a NP constituent, a series of standard combinations of Feature labels can be drawn up.

Such a set of standard combinations for an NP could be: NP ((definite, adj.-inflected) (plu 3, adj.-inflected) (inneuter, adj.-inflected) (neuter, indefinite, adj.-not inflected )). Such standard combinations can also be drawn up for other types of constituents, which are stored together in the memory part to be regarded as the sixth tabular memory (see table F).

A constituent must then satisfy at least one of the associated standard combinations. If not, the value of the probability field at that constituent should be decreased. For example, the erroneous NP constituent has "a big house" as the Characteristic field: (indefinite, sing 3, adj. Inflected, adj.-emumerative, neuter), in which none of the tried-and-tested standard combinations are found.

An error code can also be entered here in the Error message field, which is also made visible on the screen when the parsed sentence is presented.

In the next step 76, the question is asked whether the value of the Probability calibration field of the copy constituent is greater than or equal to the threshold value. In the negative answer to question (N), the copy constituent is eliminated, and the step 56 or 62 to be considered in FIG. 6 considered terminated.

In the affirmative answer (Y) to the question of step 76, the next step 77 asks whether the copy Consituent which is then regarded as the current Constituent can still be closed in view of the current threshold value. The possible functional labels for the current Constituent within the Constituent are tested on the Command field. If the present Constituent in the Stapelveld has more than one functional label (Y), this test has already been passed with a positive result in a previous stage, and therefore does not need to be repeated. Thus, as in the situation where it appears that the Constituent can still be terminated at the current threshold, proceed to step 78. Otherwise, in FIG. 7 displayed program section will then be considered terminated (N). This step can be considered optional, since it is not necessary for the parsing process, but rather accelerates the obtaining of the end result. In the next step 78, this constituent is included in Representation memory.

Using the flow diagram of Fig. 8 now follows a detailed explanation of the program section 69.

Since this program portion has many similarities with program steps 71 to 78, this will be referred to in some program steps.

At step 79 a copy is made of the Parent constituent for the purpose of the working memory, and as such is also used in the following steps.

In the next step 80 the probability factor of the copied constituent is adjusted, namely by

Probability calibration factor to be corrected with the Probability calibration factor of the constituent dominated by the Parent constituent, for example by multiplying both probability factors. To determine the new value of the probability factor, another suitable function f (x, y) can also be used from both probability factors x and y.

At step 81, the functional label, as mentioned at step 69 and at steps 99 and 104 to be described later, is included in the Stack field of the copy constituent.

Then, at step 82, a combination pair of the functional label and the dominated constituent is successively attached to the structure! elements field of the copy constituent added. .

At step 83, in the fourth tabular memory, at the category designation of the Parent constituent and the functional label of the Member constituent dominated by this constituent, a Characteristics! go through the list (see table D). All Attributes, which appear in this as well as in the Attributes list of the constituent copied in step 79, but not in the Attributes list of the Member constituent, are removed from the Attributes field of the copied constituent. In addition, all attributes present in the second Attribute list from the table, if not already present in the Attributes field of the copied constituent, are added to the Attributes field of the copied constituent. This step is similar to step 74.

At step 84, a program section is executed as also described at step 75.

The subsequent steps 85, 86 and 87, which apply to the copied constituent, are similar to steps 76, 77 and 78, provided that this is a Constituent and not a Word.

Using the flow diagram of Fig. 9 now follows a detailed explanation of the program section 37 regarding the termination of the current Constituent structure.

At step 88, the current Constituent structure, which was presented in the previous step 36 from the Temporary memory (see Fig. 3), from the Temporary Switch memory (see Fig. 4), 8 9 0 i Q 5 0 = 1 from the program section 30 (see Fig. 5) or from the program sections 103 and 108 in fig. 9 added to the Representation Memory. Since at step 65 a Constituent structure may have been created in which the Stacking field does not contain an element, it is not allowed to close such a constituent. As a result, at step 89 the question is asked whether the Stacking Field is empty. In the affirmative answer (Y), this program part is considered to have ended. In the case of a negative answer (N), in step 90 the question is asked whether the Command field of the current Constituent contains a value. If this is not the case (N), the Constituent is a Top constituent, and is not eligible for closure. At a Top Constituent, the program portion of Fig. 9 then considered terminated. If the answer at step 90 is affirmative (Y), then step 91 follows, where a Copy Constituent is made of the current Constituent. In the next step 92, the Category of the Copy Constituent, hereinafter referred to as Member Constituent, is determined. Then, at step 93, the category of the Parent Constituent is determined, based on the Member Constituent's Command Field. Then, using the data obtained in steps 92 and 93 on the category of the Member constituent and its parent constituent and on the basis of a memory part to be designated as seventh tabular memory, the corresponding grammar rule is selected in step 94 (see table G).

If the category of the Member constituent is an NP and the category of the Parent constituent is an “S”, it follows from the grammar rule NP (S, fNP) that the Member constituent can be assigned a functional label fNP. table also have more than one element.

Then, at step 95, a filtering procedure is performed, in which conditions regarding the elements in the Stacking Field are tested.

The assessment criteria are stored in the third table memory, the assessment itself being entirely in accordance with that of step 67 (see Tables C and K).

In the next step 96 it is examined whether the value in the Probability field is greater than or equal to the threshold value. After all, it is possible that in step 95 the value of the Probability field has decreased. If not (N), the program section 37 is considered to be finished. Otherwise (Y), step 97 follows, asking whether the grammar line selected in step 94 contains functional labels. If this is not the case (N), closing of the current Constituent is not possible, and the process of closing the current Constituent should be considered as ended. However, if an affirmative answer (Y) is given to this question, then at least a meaningful closure procedure is possible. It must however be ascertained whether one or more functional labels have been proposed at step 94. To this end, the next step 98 asks whether exactly one functional label was proposed at step 94. For an affirmative answer (Y), step 99 follows, and for a negative answer (N), step 100. At program section 99, for the current Constituent, eg NP, it is proposed to use the element with the functional label, ie fNP, as is indicated in the grammar rule of step 94 to function within the Constituent Structure of the Parent Constituent. The Parent Constituent is indicated in the Command field of the current Constituent. The current Constituent with the proposed functional label is then included in the Memer Field of the Parent Constituent, which has been discussed in detail in steps 79 to 83. In step 99, a copy of the parent consituent is therefore also made (as in step 79), and the functional label (fNP) at the member (NP) is therefore added to the Structural Elements field during step 82.

At step 101, it is checked whether an element has been added to the Represents memory during the program portion 99 (as explained in step 78). In the case of a negative answer (N), this program part is considered to have ended. In the affirmative answer (Y) to the question at step 11l, proceed to step 102, where the last added element is retrieved from the Representation memory, removed from the Representation memory and then subjected to the procedure with regard to the step 103 terminating this element as indicated in the sequence of steps starting with number 88. At step 100, the current Constituent structure is copied, with the Copy further considered as the current Constituent. At program section 104, it is proposed for the current Constituent to function as the element with the functional label indicated as the first element in the grammar line of step 94, within the Constituent Structure of the Parent constituent, The current Constituent with the functional proposed thereby label is then included in the Memer field of the Parent constituent in question, which is explained in detail at steps 79 to 87. At step 105, the first element (le functional element) is removed from the grammar line.

Next, it is checked at step 106 whether during the program part 104 the number of Constituents in the Representation memory has increased, which could have happened with the program part 104. In case of a negative answer (N) to this question, it is immediately returned to step 98 to perform the closing process of the current Constituent using the purified grammar rule. In the affirmative answer (Y) to the question of step 106, in the next step 107, the last added Constituent structure is retrieved from Representation memory and removed from it and considered as the current Constituent, whereupon in the next step 108 the termination program is indicated by the series of program steps starting with number 88 applies. After step 108, the program returns to step 98.

Since temporary labels may have been assigned during the previous program, these temporary labels will be replaced by final labels in connection with the actual parsing process in the following program section. For example, for the Sample Grammar used here in all Constituents stored in Representation Memory, the fNP labels will be replaced, where possible, by the final labels Subject (Subject), Direct Object (Object), Indirect Object Object) and Predicate (Predicate), which are respectively used under the following abbreviations: Subj., Qbj., Indobj., Pred.

To this end, at step 109, the count position of the m * -teler, with which a reference to the rank number of a constituent is obtained, is reset to 0, after which at step 110 the count position of this counter is increased by "1".

In step 111 it is checked whether the count of the m * -teil has already exceeded the maximum value (m * max) corresponding to the number of constituents. In the affirmative answer (Y), this program section is considered to have ended. In the negative answer (N) of the question at step 111, the next step 112 asks whether the Command field of the m * -th Constituent structure contains a data. If the question is answered in the affirmative (Y), then it is not a Top Constituent, and it is therefore not necessary for definitive labels to be assigned.

If the question is answered in the negative (N), program phase 113 follows with regard to replacing the provisional functional labels with final ones, after which the program returns to step 110.

With reference to Fig. 11 now follows a more detailed explanation of program phase 113.

At step 114, an n-counter, the count of which refers to the rank of the member pair in the Structural Elements field of the current Constituent, is reset to 0. Then, at step 115, the count of this counter is increased by "1".

In the next step 116, the question is asked whether the count of the n-counter has already exceeded the maximum value (nmax), which corresponds to the number of member pairs in that Structural Element field.

If this is the case (Y), the program portion 113 is considered terminated, and the program goes back to step 110. If the question (N) is answered negatively at step 116, the second element of the next step 117 becomes the pair of the current Constituent determined by the counting position of the n-counter, and designated as the current Constituent. In the next step 118, the question is asked whether the element designated as the current Constituent is indeed a Constituent, and not a Word. If not (N), the program goes back to step 115. If it is (Y), the current Constituent becomes on its structure and therefore on the contents of the Stack field of the current one, i.e. Constituent designated at step 117, examined. This implies that the same procedure as described at steps 114, 115, 116, 117 and 118 must now also be carried out again within the program part 119 with steps 120, 121, 122, 123 and 124, but now on the Member pairs of the element designated as the current Constituent. The rank number of the member pair is indicated here with n *. Should one of the Member pairs have a second element, which does not represent a Word but a Constituent (which may be the case with relative clauses, for example), then the next step 125 must also be replaced by a program section marked with indication 119. In this description, the situation is examined, in which the second element is designated as Word for all Member pairs at step 118. The consequence of this assumption is that step 119 can actually be omitted and the program ends up at step 126, where the question is asked whether one of the elements on the Stack field of the Constituent selected at step 118, namely the second element of the nth pair, is a temporary label. If this is not the case (N), the program returns to step 115. In case of an affirmative answer (Y) to the question in step 126, a program part follows in step 127, where the temporary functional label is replaced by a definitive functional label. The contents of the Stack field of the m * -th Constituent structure are thereby examined, and this content is compared with certain grammar rules, which are stored in a memory section to be designated as eighth tabular memory. Such a rule could be: ((fNP, Vfjn_ main, Smod, fNP, Endmark) (Subj., Obj.), Which means that the first fNP is replaced by a label "Subject" and the second fNP by a label "Suffering Object" (see table H).

If a number of solutions occur with a certain data content of the Stack field, this leads to a corresponding number of Top constituents, all of which are written down in the Representation memory. This is done by copying the current structure with the preliminary functional labels.

First of all, the provisional functional labels in the Structural Elements field of each Summit Constituent are now replaced in a corresponding manner.

Then, at step 128, a filtering process is performed using a ninth tabular memory to be designated (see Table I), verifying whether the conversion of preliminary functional labels generated by the grammar rule of this program section is permitted is based on the obligatory agreement of certain elements in the Characteristic Field for some related Constituents. In particular, there is such a relationship between the Constituent structures "Subject" and "Verb", where the inflection indication should be consistent. Table I lists the appropriate grammar rules, which are arranged according to the category designation of the constituent to be examined. Each grammar line also contains a list of elements and a list of characteristics. The Characteristics field is retrieved from each structure (Constituent or Word), which corresponds to one of the elements that appear on the list. The intersection of all these Attribute fields with each other and with the found list of Attributes cannot be empty.

For example, in the sentence "He walk", the cross section of the Characteristics of the "Subject" with the found list of Characteristics will yield "sing 3", after which the cross section will become empty by entering the Characteristics of the "Verb". There is thus an ungrammatical sentence construction. The analysis obtained is now made less likely by decreasing the value in the Probability field, while also providing the Error message field with an error code.

After the filtering process, the program returns to step 115. Steps 129, 130 and 131 are the same as steps 126, 127 and 128. After the "syntax directed parser", a "syntax embedded parser", which operates according to the described inventive idea, are explained. The latter parser differs from the former parser in that the steps to be performed with a tabular memory are replaced by actions to be carried out programmatically. As an example, program step 75 (Fig. 7) will be considered, with part of the contents of Table E in the flow chart of Fig. 12 is shown.

In FIG. 12, at step 132, the question is posed as to whether the constituent is of the category "S". If this is the case (Y), program section 133 follows, after which the program of step 75 is considered terminated.

If not (N), step 134 follows, where the question is asked whether the constituent is of type Srei. If this is the case (Y), then a research program 135 aimed at it follows. If this is not the case (N), then step 136 follows, where the possible processing phase starts at the constituent Scomp using step 137. "

The following program section 138 concerning an NP constituent with the associated research program will now be explained in more detail. At step 138, the question is asked whether the constituent is an NP. If the answer to this is affirmative (Y), program step 139 follows, where the question is asked whether the functional label "head" occurs twice in a row. If this is the case (Y), program step 152 follows, where the value of the Probability calibration field is decreased by a certain correct factor, after which the program proceeds to step 140. If the question at step 139 is answered negatively (N) , one or more similar questions follow, which are not further explained here, but which ultimately end up in program step 140. The question is asked whether the functional label "head" is followed in the constituent to be examined by the label "det". If this is the case (Y), then this is an incorrect sequence, and in the next step 141 the value of the Probability field is corrected by a certain factor. In the negative answer (N) of the question at step 140, step 142 follows with the question whether the functional label "head" is followed by the label "nmod-a". If this is the case (Y), in step 143 the value of the Probability field of the Constituent to be examined is decreased by a certain factor. If there is a negative answer (N) to the question at step 142, a similar question is processed in a next step. Eventually, and therefore also after steps 141 and 143, the program then arrives at the first step 144 of the next phase of the research program, where the question is asked whether the label "det" occurs only once in the constituent. In the case of a negative answer (N) to this question, the value of the Probability field is decreased by a certain factor in the next program step 145. In the affirmative answer (Y), step 146 follows, where the question is asked whether the constituent contains only one functional label "head". If not (N), a decrease of the Probability field value is made at step 147. After the program steps to be performed in this phase, the program run at step 75 is considered completed. If the question is answered negatively (N) in step 138, then step 148 follows where the question concerns a PP constituent. Upon confirmation (Y) of the question at step 138, a related research program is run. A similar program portion but for an AP constituent occurs at steps 150 and 151, after which the program equivalent to step 75 of FIG. 2 is considered terminated.

A similar programmatic treatment is also possible for the other tables of the "syntax directed parser".

The program sections, which relate to steps 67, 75, 84, 95, and 128, use flutter procedures that determine whether or not the sentence entered is grammatically correct, based on certain criteria derived from grammar rules . If this is not the case, the sentence is provided with an error message or error code and a lower probability calibration factor, which, for example, when the sentence is selected in step 44, is displayed by the system on a screen. The operator of the system can still correct the entered sentence manually.

A system that parses and automatically corrects the entered sentence is considered desirable. This enhancement function is to be performed as program stage 153 after step 4, in the absence of a useful result. In the next step 154 the question is asked whether the non-grammatical sense has improved sufficiently, which can be seen from the value in the probability field. A negative answer (N) to the question of step 154 then implies that the sentence presented cannot be sufficiently corrected. The program will then return to step 1 for the operator to type in a modified version of the present sentence. In the affirmative answer (Y) to question 154, the program proceeds to step 4.

The basic idea behind program phase 153 will now be explained with reference to Figures 13, 14 and 15. In order to still have both the original representation and the improved representation after the correction action has been completed, a copy is made in step 155 (see Fig. 13) of the selected, original sentence representation in the representation memory, which is then turned on during phase 156. a correct procedure is submitted.

In the subsequent step 157, a number of fields of the selected top constituent are adapted to the change made.

This applies, for example, to the assignment fields of the member constituents belonging to this top constituent and also to the dependent member constituents. These command fields are now filled with an indication or reference to the relevant parent constituent, after which the program proceeds to step 154.

The program phase 156 is divided into a number of program steps as shown in Fig. 14.

Since the program phase 156 is to be passed only by the top constituent and by the member constituents with an incorrect structure, the program will start at step 158 with the question whether the constituent presented has a probability factor less than the value 1. In the case of a constituent with a correct structure, this is answered negatively (N). Thus, the actual correct program will not be executed and the program proceeds to step 157. As will be seen below, step 158 may also follow after step 164, which will then result in the program continuing after step 158 with step 161. For a constituent with an incorrect structure, the question is answered in the affirmative (Y), and the program proceeds to step 159, where the probability field takes the value 1. After all, it would not be correct if the present constituent had an uncorrected probability factor after correcting the constituent itself or its member constituents. Correcting a sentence structure will start at the lowest level in a sentence, on which there are still constituents. In order to descend to that level in a sentence structure, a counter (r counter) is reset to 0 (r = 0) in the next program step 160, after which the counter reading of this counter is increased by 1 in the next step 161 ( r = r + 1). In the subsequent step 162 it is checked on the basis of the condition r <_ rmax whether the r-counter has a count which is less than or equal to the number of member constituents in the present constituent. If this is the case (Y), then in step 163 the constituent determined by the r-counter is taken from the word memory of the system and in step 164 the question is asked whether this constituent is indeed a phrase constituent (and therefore not a word constituent). If this question is answered in the affirmative (Y), then the sentence structure should descend to an even lower level, and the program will proceed to step 165. This step therefore implies that for that sentence constituent, the correction program starts as the current constituent step 158 will be gone through again. However, if the constituent falls under the "Words" category, and the question of step 164 is answered in the negative (N), then the program returns to step 161.

If the question is answered in the negative (N) at step 162, then the present constituent has a constituent structure, in which only words occur as member elements. In the subsequent step 166 it will be examined in the present constituent whether the associated error message field has one or more error messages. If this is not the case (N), then for that constituent the correction process has ended and the program proceeds to step 173. If the question in step 166 is answered in the affirmative CY) »then step 167 follows, where the values of the probability! calibration field, the attributes field and the error field of! the current constituent will be adapted to the changes that have already taken place during the correction phase. This is by no means imaginary since step 165 shows the full correction phase of FIG. 14 Means, and precisely at step 172 the actual correction of the sentence structure takes place. Since program steps 67, 75, 84, 95 and 128 result in a number of (1) types of error messages in the form of error codes, and each type of error message has a correction function characteristic of the respective error, the current constituent on the possible error messages or error codes are investigated in the error reporting field.

At step 168, a t-counter, the count of which corresponds to a certain rank number in a possible series of error codes in the error message field, will be reset (t = 0). Then, at step 169, the counting position of the t-counter will be increased (t = t + 1), and at step 170 the question will be asked whether the counting position of the t-counter is higher than the number, which is the number error codes (½ ^) in the error message field (ΐ> ίπ, 3χ). If this is not the case (N), then in step 171 the error code corresponding to the count of the t-counter will be retrieved from the error message field, and in the subsequent step 172 the correction function valid for that error code will be applied to the current constituent are applied. Step 172 will be explained in more detail with reference to FIG. 16 are explained. Then, the program returns to step 169.

On the other hand, if the question is answered in the affirmative (Y) at step 170, and therefore all error codes have been settled with that constituent, the program proceeds to step 173, where an identical program as in step 167 is executed. After going through step 173, if at least the correcting function (Fig. 14) is part of step 165, the program returns to this step and then continues with step 161. However, the correcting function (Fig. 14) does not become part of step 165, the program proceeds to step 157 after step 173.

If the question is answered negatively (N) at step 158, when the correcting function of FIG. 14 is part of step 165, back to this step. If not, the program proceeds to step 157.

Steps 167 and 173 need further explanation, which will be explained with reference to FIG. 15 will be made. The function of these steps involves adjusting the probability field, the error field and the characteristic field of the current constituent in the created situation. Use is made here of the functionality as described in program steps 67, 74 and 75. The adaptation of said fields starts with the assignment of an initial value to these fields. Thus, the probability field at step 174 is assigned the value "1", the error field at step 175 is assigned the value "NIL", and the attribute field at step 176 is the complete list of possible occurrences as indicated in Table A under the heading of the current constituent . These fields can be subject to change, especially with regard to the characteristics field. Matching these fields to the member elements starts at step 177, where a count unit (u-counter), the count of which corresponds to the rank number of the member element within the current constituent, is reset to 0 (u = 0). Then, at step 178, the count of the u-counter is increased (u = u + 1), and at step 179 the question is asked whether the count of the u-counter exceeds the number of member elements (umax) within the current constituents (u> umax). If there is a negative answer (N) to this question, program step 180 follows, where the currently valid value of the probability field for that constituent is multiplied by the value of the probability field of the relevant member constituent. In case the member constituent is a word, the fictitious value 1 applies here.

Then, at step 181, the value of the attribute field is adapted to the data associated with the present member element. This adjustment is made using Table D in a manner identical to step 74.

If in step 179 the question is answered in the affirmative (Y), then in the next step 182 on the obtained constituent structure, by means of some control e-operations, certain filter functions as described in step 75 are performed. This is also the case in the next step 183, which is similar to step 67.

The constituent structure is thus prepared in order to be able to make corrections thereto or to obtain a correct representation of the constituent.

In the program step 172, a number of specific correction procedures are completed, which are performed according to a program shown in Fig. 16. After step 171, the program proceeds to step 184, where the question is asked whether the error message with rank number t from the current constituent (see step 171) corresponds to an error message of certain quality associated with that step. If the question is confirmed (Y), step 185 follows, in which the correction determined in step 184 is performed on the current constituent. For example, step 184 may be assigned the function of correcting a constituent in which an incorrect order of member elements has been detected. Such a correction will be made with reference to FIG. 17 are outlined. After step 185, the program will proceed to step 169. If there is a negative answer (N) to the question in step 184, step 186 follows, where the question is asked whether the error reporting element with rank number t corresponds to a certain type, linked to that step error reporting element.

If that question is answered in the affirmative (Y), step 187 follows, in which another type of correction, for example taking certain measures in a constituent as a result of an incorrect number of functional labels, is performed on the constituent. This error correction will be based on FIG. 18 are outlined. After step 187, the program will proceed to step 169.

It is investigated in the manner described which correction measure is and will be implemented for a certain error message.

Apart from the ones shown in FIG. 17 and 18, corrective measures to be explained with reference to FIG. 19 to 25, other corrective measures are described, which are shown in FIG. 16 are under discussion. At the correction phase in Fig. 17 it is assumed that both the error message itself, in this case denoted by "COA", as well as the element pairs to be exchanged are stated in the error message field of the current constituent. This correction phase starts with step 198 with the question whether there is still an error message of the type "COA11 present in the error message field. In case of a negative answer (N) of this question, the program goes to step 169 (see Fig. 14), and upon an affirmative answer (Y) to step 199, where the exchangeable element pair from the error message field is transferred to the working memory In the subsequent stage 200, the relevant elements in the stack field are exchanged, which is also the case in the next step 201 for the structural element field Then it must be determined whether the result obtained is correct in order, for this purpose the relevant "COA" entry is removed from the error message field in step 202 and the entered value is replaced in the probability field in the next step 203 by the value "1." Then, in step 204, the checking procedure is carried out as in step 75, and in the next e step 205 checking whether the constituent meets the condition for closing a constituent, as it was the case in step 67. As a result of these two steps, the probability field and the error message field are adapted to the new situation. After step 205, the program returns to step 198, where the question regarding the new situation is repeated. The result obtained is always fed back to the representation memory. If the question in question 186 is answered in the affirmative, the correction phase indicated by number 187 is initiated, the program of which is shown in FIG. 18 is shown.

This correction phase deals with the errors, which relate to an incorrect number of functional labels within a sentence or phrase, as determined at step 75. It is assumed that the error message itself, in this case denoted by COB, the relevant functional labels, the maximum number that such a label may occur, and sometimes a label, which must be present urgently, in the error message field of the current constituent are listed. This correction phase starts with steps 206 and 207, in which the error message field and the stack field are successively copied to the working memory. Then, in step 208, the conscious error message is retrieved from the error message field. In the next step 209, a certain flag (or optionally a changeable label) is added to the information in the working memory and the value "NIL" is assigned. In the next step 210 it is checked whether or not the error message comprises three elements. It is assumed here that in addition to the event-dependent error messages described in step 75, event-dependent error messages also occur. An event independent error message only indicates that the occurrence of a certain label in the constituent is limited to a maximum.

For example, (det, 1) indicates that a determiner may only occur once in that constituent. We are dealing here with an error message of 2 elements. An event-dependent error message indicates that only for a certain event applies that the occurrence of a certain label in the constituent is limited to a maximum. For example, the error message (Vfin intr., FNP, 1) indicates that in the presence of an intransitive verb form in the sense, the present constituent may contain only one fNP. This allows phrases such as: "He walks the city" to be recognized as incorrect by the system, after which the operator can correct the sentence by including a preposition (in, to, by) in the last POI. This is a 3-element error message.

At step 210 the question is asked whether this is a 3-element error message: If this question is answered in the negative (N), the program goes to step 211. On the other hand, if the question is answered in the affirmative (Y), step 212 follows. where the question is asked whether the label (the third element), which represents the event, is still present in the stack field, and has not been removed from it earlier. If you have an affirmative answer (Y) to the question at step 212, the program goes to step 214 to examine whether an error correction should be made. In step 211 as well as in step 214, the question is asked whether there are still more than the permitted number of the type of functional label in question. If this is not the case (N), the program goes to step 213, where the flag (or label) entered in step 209 is assigned the value "TRUE" (and therefore indicates that the error message is no longer real. negative answer (N) from step 212, the error message is no longer real, and the program will proceed to step 213. On the other hand, if the question in step 211 or step 214 is answered in the affirmative (Y), the program proceeds to step 215, respectively. 216, where the flag (or label) entered in step 209 is assigned the value "NIL".

At step 217, which follows steps 215, 213 and 216, the question is asked whether said flag (or label) has the value "TRUE". If that is the case (Y), then there is no longer a real error message, and in step 218 the error message itself (COB) will be removed from the error message field, and in the next step 219 the remaining part of the error message will be removed. turn into. This is followed by step 169. If a negative answer is obtained in step 217 (N), and so there are too many functional elements of the same conscious type, in step 221 the superfluous element pair is removed from the structural element field and in step 222 the corresponding element removed from the stacking field. It can be taken as a starting rule that the last element (s) always represents the superfluous part. In addition, a more targeted removal of the redundant element could be achieved on the basis of considerations such as "with which noun does the article correspond" or, "which noun corresponds to the personal form".

After step 222, the program returns to step 210 to determine if there are still too many labels of the functional type in question. If the question at question 188 is answered in the affirmative (Y), the correction phase indicated with number 189 is started, the program of which is shown in FIG. 19 is shown.

This correction phase deals with the errors related to an error message obtained by checking one or more incorrect combinations of features in the feature field. This check was performed using the first series of combinations in Table F at step 75 or 84. Therefore, in the example described there, none of the elements from the combination proposed by table F (neuter inneuter) was present in the characteristic field. The error message field will therefore contain the error message (COC) to be used with this type of error and the corresponding combination of characteristics (neuter inneuter).

At step 223 the conscious combination (neuter, inuter) is removed from the error message field and put into the working memory.

Then, at step 224, from a priority table L which is stored in a ninth tabular memory, that list of elements is selected, which contains the elements of the constituent and which assigns a priority order to these (functional) elements. This order of priority indicates how the various elements must be adapted to each other and therefore corrected. In the case of the word combination "the house" as NP, a tenth tabular memory will indicate the priority order (head determiner), so that the article must be adapted to the noun.

In the next step 225, an auxiliary variable HLP is invoked, which receives the value of the combination copied in step 223, in this case (neuter, neuter).

In the subsequent program phase, the main characteristic in the variable HLP is selected in the priority table L in accordance with the importance of the elements as indicated. In the example "the house" at step 75, it boils down to this, that because of the word "house" the main element will be "neuter" from the combination (neuter, inuter), and that the other elements belonging to that constituent will remain accordingly Accordingly, at step 226, a counting unit (v-counter), the counting position of which corresponds to the rank number of an element in the list selected in step 224 within the priority table L, is reset (v = 0). step 227 the counting position of the v-counter is increased (v = v + I), after which in step 228 the question is asked whether the counting of the v-counter is the number of elements (Vmax) of the selected list in the priority table L If this question is answered in the affirmative (Y), step 229 follows. In the case of a negative answer, step 230 follows, in which the element determined by the counting of the v-counter in the selected list of the priority table w is selected. Then, at step 231, a counting unit (w-counter), the counting position of which corresponds to a certain rank number in the series of elements in the present constituent, is reset to the starting position (w = 0). In the next step 232 the count position of this counter is increased (w »w + 1), after which it is examined in step 233 whether the count position of the w counter has exceeded the number of elements (w ^) from the constituent. If this question is answered in the affirmative (Y), the program returns to step 227. In the case of a negative answer to this question (N), in the next step 234 that element is selected from the stack field, the rank number of which corresponds to the count of the w counter.

Depending on the selected grammar chosen, the next step 235 may or may not be included in the program. In an example grammar, in which the category of a constituent is further described by means of certain associated characteristics, mandatory errors can be assigned to certain error messages. For example, if for the constituent "the house" the category designation "neuter" of "house" is supplemented to NP neuter, this creates the imperative requirement that the entire constituent must be written in the "neuter" form. In other words: The error reporting field does not write the conflicting combination (neuter inneuter) but the prescription "neuter". In this case, at step 235, the question is asked whether the list included in the error message field contains only one element, i.e., prescription. If this is the case (Y), step 229 follows, in which the control measure still asks whether the variable "HLP" still contains an element. If "HLP" does not contain an element (N), then the program of FIG. 19 ends, and the program proceeds to step 169.

If, on the other hand, the question is answered affirmatively (Y) in step 229, then step 236 follows. If the question is answered negatively (N) in step 235, step 237 follows.

In case error messages are always generated on the basis of combinations of characteristics, for example from table F, step 235 can be omitted, and step 234 immediately follows step 237. At step 237 the question is asked whether the count of the v-counter (see step 226) labeled element (functional label) from the priority list of table L is equal to the functional label from the current counter counted by the count of the w-counter (see counter 232). If this is not the case (N), it is returned to step 232. If the question is answered in the affirmative (Y) in step 237, then in the next step 238 the common part of the list of features associated with the count of the w-counter (see step 232) determined from the structural elements field and from the list copied from the error message field in step 225 and assigned as a replacement value to the variable "HLP". In the present case, the value (neuter inuter) for the variable HLP will be replaced by "neuter", since in step 225 the selected list from the priority table L gave a reference to "head" and therefore to "house" with the attribute " neuter ".

In the next step 239 the control question is asked whether the variable HLP has obtained a real value in step 238, and is not, for example, empty. If this question is answered in the negative (N), then step 240 follows. Since the HLP variable cannot make a proposal here, according to which the correction of the present constituent should take place, the HLP variable is used for the further course of the program is nevertheless assigned a value, namely the first element of the combination obtained in step 243 or 225. Then, the program goes to step 236.

If the question is answered affirmatively (Y) at step 239, step 241 follows, asking whether the value of the HLP variable determined at step 238 comprises multiple elements. If not (N), step 242 follows, where the first element of the combination determined in step 238 is assigned as new value to the variable "HLP". Then the program proceeds to step 236.

If the question is answered affirmatively (Y) in step 241, then in the next step 243, the list retrieved from the error message field in step 223 is replaced by the value of the HLP variable obtained in step 238.

Then, the program proceeds to step 232.

At step 236 a function LHF is called, which will adapt the structure of the current constituent in such a way that the characteristic determined by means of the HLP function (see step 240 and 242 respectively), in this case “neuter” 1, may be assigned to that structure and will be awarded. The function to be called with step 236 will be described with reference to FIG. 25 will be explained in more detail.

After step 236, at step 244, the question is asked whether the error message field of the current constituent still contains an error message of the COC type. In the affirmative answer (Y), the program returns to step 223, and in the negative answer (N), to step 169 (see Fig. 14). At fig. 19 and furthermore with the figures 20 and 23 still to be discussed, the function LHF mentioned at step 236 is invoked, which reference is made with reference to FIG. 25 is explained and which starts at step 245 with the question whether the current structure relates to a word. If this is the case (Y), then in the next step 246 a different form is searched for the current word in the lexical memory, which does correspond to the characteristic determined by the HLP function. Then the program returns to the program section that it had left.

In the negative answer (N) to the question at step 245, a number of fields of the constituent are brought into the initial state. This means that at step 247 the probability field is assigned the value "1", at step 248 the error message field is assigned the value "NIL", and at step 249 the characteristic field the attributes belonging to the category as mentioned under table A. Then, at step 250 assigned to a variable denoted by "GRAM" the attributes listed in the Table of the current constituent category and functional label.

Subsequently, the various elements (members) of this constituent must be adapted to the characteristic determined by the HLP function in this case "neuter". For this purpose, at step 251, a counting unit (s-counter), the counting position of which corresponds to the rank number of the member elements in this Constituent, is reset to the initial value (s = 0), after which at step 252 the counting position of this counter is incremented (s = s + l). Then, at step 253, the question is asked whether the count of the s-counter has exceeded the number of member elements (smax) within this constituent. If this is the case (Y), then step 254 follows. If the question of step 253 is answered in the negative (N), then step 255 follows, whereby the member element of the Constituent corresponding to the count of the s-counter is taken from the representation memory retrieved and written into working memory.

In the next step 256, the question is asked whether the member element determined by the count of the s-counter within the Constituent can be assigned the characteristic "neuter" in the present case and does not already possess it. For example, in the NP-Constituent "the big, beautiful house" the article "de" will give an affirmative answer, since in table D under "NP" and "determiner" the attribute "neuter" belongs to the possibilities.

Via steps 258 and 245, at step 246, its equivalent with the attribute "neuter" will be searched, resulting in the word "it". Subsequently, for the next combination "large, beautiful" with the label nmod-A, no reference to nmod-A will be found in table D, so that the question of step 256 will be answered negatively.

In the next step 257, the feature field of this member element is adjusted using Table D as set out in step 74. The word "house" already has the attribute "neuter" and will thus proceed to step 257 after step 256.

In the affirmative answer (Y) of the question at step 256, step 258 follows where the function LHF to be described in this figure is performed again. The final result of this function always lies at step 246, where the adapted lexical form for the then applicable member element is chosen.

If the member element has a word structure, the assignment field must still be completed. To this end, a corresponding question is asked at step 259, and at the affirmative answer (Y) at step 260, the pointer to the parent constituent is entered in the command field. Then, the program goes to step 257.

If there is a negative answer (N) to the question at step 259, the program goes directly to step 257.

If the question in question 25 is answered in the affirmative (Y), then it must be determined whether error messages regarding the changed constituent should still be included in the error message field.

For this purpose, at step 254 and then at step 261, some filter operations are performed, which have already been described in steps 75 and 67, respectively. After this, the program returns to that place in the program, which it performs for the purpose of executing this LHF function.

If the question is answered in the affirmative (Y) at step 190, the correction phase designated with number 191 is initiated, the program of which is shown in FIG. 20 is shown.

This correction phase deals with errors, which relate to an unauthorized combination of features, as determined in step 75 or 84 on the basis of table F. This correction phase also comprises an important part, in which the desired characteristic must then be determined. This assumes that both the error message itself, namely "COD", as well as the features to be replaced, are listed in the error message field of the current constituent. This correction phase starts with step 262, in which the second element of this error message is transferred from the representation memory to the working memory. Then, in step 263, from table F, the list of legal characteristic combinations belonging to said second element and to the constituent category is retrieved and assigned to a variable "FTRLSTS" in the working memory. In the next step 264, the function "FFTC" is invoked, which on the basis of the list of legal characteristic combinations and the characteristics present in the characteristic field of the constituent yields the desired characteristic. The function "FFTC" is shown in Fig. 24 explained in more detail.

Then, at step 265, using the function "LHF" (see Fig. 25), the desired attribute is added to the current constituent. A word will be replaced by another form of the word.

The function "FFTC" in Fig. 24 uses two arguments, namely the list of allowed attributes from table F and the list of attributes from the characteristic field, which are stored in working memory at steps 266 and 267.

In the next step 268 it is checked whether the variable "FTRLSTS", which still had the complete list of allowed feature combinations in the initial phase of executing the function "FFTC", still has such a combination. In the negative answer to this question (N), the program of FIG. 24 is performed, and return to FIG. 20 to perform step 265. In the affirmative answer (Y) to the question at step 268, the next step 269 asks whether all elements of the currently applicable feature combination with the exception of the last element in that combination, also appear in the list of current features (see step 267). In the negative answer (N) to this question, in the next step 272, the first currently occurring combination on the list of allowed characteristic combinations is removed, and the program proceeds to step 268. In the affirmative answer (Y) on the question at step 269 in the next step 271, the last element from the (first) feature combination examined is designated as the desired feature.

For example, is there only one legal combination of features left for the variable "FTRLSTS", in this case "neuter indefinite adj-not-inflected" (see table F), and "neuter" and "indefinite" also appear on the list of current features ( see step 267), then the last element, in this case, "adj.-not-inflected" is the desired attribute. The program of FIG. 24 is thus also terminated, and then proceeds to step 265 of FIG. 20, after which this correction phase is exited, and the program returns to step 169.

In the affirmative answer (Y) to the question at step 192, a correction phase indicated by step 193 follows, the program of which is shown in FIG.

21 is shown. This correct phase deals with error messages generated by steps 67 and / or 95 due to the lack of an essential element, such as a definite article in some NPs. The occuring phase of the relevant constituent did result in a decrease of the probability factor with the generation of an error message COE. This error message, as well as the deliberate combination of list segments, which have resulted in this error message, are transferred to the working memory at step 273 of the error message field. In the next step 274 it is checked which functional label is missing in the second Rice segment. Although usually only one label fills this list segment, it is possible that multiple labels may appear therein. For this purpose, a counting unit (p-counter), the counting position of which corresponds to the rank number of a functional label in the second list segment, is reset to the initial value (p = 0). After this, the p-counter is incremented at step 275 (p = p + l), and at step 276 the question is asked whether the count of the p-counter already exceeded the number of functional labels (ρ ^ χ) in the second list segment has (p> PmBx) · If the case is (Y), the program proceeds to step 169, if not (N), step 277 follows, selecting the pth element in the second list segment. In the next step 278 it is checked whether that p-th element does indeed occur in the Stack field. (To this end, the elements of the stack field will be compared one by one with the pth element, and if up to the last label of the Stack field a non-identity between the elements to be compared is determined, the pth element is missing. the Stapelveld).

If the presence of the pth element is determined at step 278 (Y), step 275 follows, if not (N), step 279 follows.

When the pth element, which functions as a functional label, is determined as a missing element, this label can be added to the Stacking Field. However, a matching word structure or constituent structure is still missing. In practice, this usually concerns a word structure. The matching word structure is obtained by checking in table B which word category is allowed for a given parent constituent and functional label of the missing member element, and then by selecting the first word in lexical memory that meets this requirement. To this end, a counting unit (a-counter) first becomes at step 279. whose count position corresponds to the rank number of a certain combination in the tabular memory classified according to table B, returned to the initial position (g = 0). Then, at step 280, the count of the g-counter is increased (g = g + 1), and at the next step 281 it is checked whether the count of the g-counter exceeds the number of grammatical lines in the table memory in accordance with the table. B has been released. If this is the case (Y), the program goes back to step 275, if it is not (N), step 282 follows, where it is checked whether the grammatical line has the missing functional label, from which the word category then follows. For example, if in a NP the functional label "det" is missing (see steps 67 and 95), it follows from the first grammar line "article" (NP (det)) "that a word category" article "is possible in the constituent.

If the correct grammar line is not detected at step 282 (N), the program returns to step 280. Otherwise (Y), at step 283 in lexical memory the first word structure of the found word category is searched, and the stack field and the structural element field supplemented with the relevant functional label, respectively with that label and the word structure found.

Then, at step 284 at the current constituent, the probability, error and field and attribute fields will be adjusted to the current situation, as explained at steps 174 through 183 (see FIG. 15). After that, it is still necessary to check at step 285 whether the newly entered element is in the right place, which implies that a program phase is completed as described in steps 198 to 205 (see Fig.

17), then the correct phase of error "COE" has ended, and the program proceeds to step 169.

If the question is answered in the affirmative (Y) at step 194, the correct phase indicated by number 195 is initiated, the program of which is shown in FIG. 22 is shown.

This correction phase is in fact a counterpart to that associated with the "COE" error message. In the correction phase to be considered here there is an unnecessary element, which was also determined in step 67 and / or 95 on the basis of table K. The error message itself, in this case "COF" and the list of unnecessary functional labels are added in step 286 retrieved from RAM from the error message field.

Then, at step 287, a counting unit (q-counter), the counting position of which corresponds to the rank number of an element in the list of redundant functional labels, is reset to the initial value (q = 0), and at step 288, the counting position is of the q counter increased (q = q + I). Next, it is checked at step 289 whether the count of the q-counter has not already exceeded the number of elements (qmax) in the third list segment of the relevant grammar line. If this is not the case (N), the relevant element is removed from the stack field during step 290, and the relevant pair of elements from the structural element field during step 291. The program then returns to step 288. If the question in step 289 is answered in the affirmative (Y), in step 292 the probability field, the error message field and the characteristics field will be adapted to the current situation in the current constituent, as in the steps 174 to 183 (see Fig. 15) are set forth. This corrective axis is then exited and the program returns to step 169.

If the question in question 196 is answered in the affirmative (Y), the correction phase indicated with number 197 is initiated, the program of which is shown in FIG. 23 is shown.

This correction phase deals with errors related to a missing feature in the error reporting field, which was determined at step 128 with reference to Table I. This is based on a fairly detailed error message, which in addition to the error message "C0G" also includes the functional label of the structure to be corrected and the missing feature. For the example at step 128 this was: (Vfin main, sing 3). At steps 293 and 294 the Table "vfin main" and the missing attribute "sing 3" are successively removed from the error reporting field. The label corresponds to a certain constituent or word structure, in this case "walking", in the structure element field.

This structure is retrieved at step 295. Then, at step 296, the function "LHF" is performed, which is illustrated with reference to FIG. 25 has already been explained. In this case, in the aforementioned case, the structure "walk" will eventually be replaced by "walk", which corresponds to the characteristic "sing 3". Subsequently, the higher constituent must be adapted to the entered change, for which purpose the error field of that constituent is cleared in step 297 and the probability field in step 298 is assigned the value "1". Then, at steps 299 and 300, some control operations are applied to the current constituent, which have been successively described at steps 75 and 67, respectively. After this, this correction phase is exited and the program returns to step 169. A particular application of the described parser and the associated correction procedure is obtained when replacing words in a text with other words. Certainly in a multi-author system, in which multiple persons make their own text contribution to a large document, it is possible that the word usage in the document is not consistent due to the individual contribution of the persons. In order to get consistent word usage in the document, certain words need to be replaced by others. Replacing one word with another can have some consequences. Substitution of a neuter noun by a noun of the non-neuter type sometimes requires modification of the article or adjective. Also, sentence adjustment is needed when a singular subject is replaced by a plural subject.

The replacement procedure starts with step 301 (see Fig. 26), in which the replacement word and the word to be replaced are written into the working memory. At step 302, the word structure for the replacement word is extracted from the lexical memory and written into the working memory.

Then, at step 303, the program goes through the text to stop at the first sentence containing the word to be replaced.

At step 304, the question is asked whether a parsing result of this sentence is already stored in memory.

If yes (Y), then the program goes to step 305, otherwise (N) to step 306, parsing the sentence and then the program goes to step 305. In the first place, it is checked if a matching word category can be found for both words. There is also the possibility that, despite a difference in word category, there may be a similarity in the functional label. For example, the word categories "noun" and "pronoun substantive" have the same labels in the grammatical lines as shown in table B. Therefore, a "noun" in a POI labeled "head" can be exchanged for a "pronoun substantive". Similar possibilities apply to an "article" and a "pronoun adjective". It is therefore possible to investigate whether the combination of a constituent and functional label determined by the parser also occurs in grammar lines in one of the word categories of the replacement word structure.

Since the replacement word has to be viewed for each occurring category, in step 305, resetting to the 0 position occurs at a z-counter (z = 0). The count of the z-counter corresponds to the rank number of the word category, as occurs with a word structure in the lexical memory. Then, at step 307, the count of the z-counter is increased (z = z + l), and at step 308, the question is asked whether the count of the z-counter has exceeded the number of occurring categories for the replacement word (z > zmax). If not (N), then in step 309 in the tabular memory with the information about table B, the collection of grammar lines is selected for the word category determined by the counting of the z-counter. Within this collection, each grammar line checks whether the same label is possible for the present word category within the constituent in question. For this purpose, a counting unit (h-counter) is reset at step 310 (h = 0), and the counting of this counting unit is increased at step 311 (ih = h + 1). Next, at step 312, it is checked whether the count of the h-counter is greater than the number of grammar lines in the present word category. If that is the case (Y), then the program goes back to step 307, if it is not (N), the program goes to step 313. In step 313, within that collection of grammar rules, the line whose rank number corresponds is selected with the count of the h-counter, and at step 314 it is checked whether the parent constituent and the functional label in that grammar line correspond to that of the word structure to be replaced.

If this is not the case (N), the program goes back to step 311. However, if this is the case {Y), step 315 follows, examining whether the conscious word category of the replacement word also corresponds to that of the word to be replaced. If this is the case (Y), the program goes to step 316, where the replacement word with the subject word category and its attributes is written in a first buffer. If the question is answered in the negative (N) at step 315, then step 317 follows, in which the replacement word with the present word category and the associated features are written in a second buffer. After step 316 or 317, the hpt program returns to step 307.

If the question is answered in the affirmative (Y) at step 308, the next step 318 (see Fig. 27) asks whether no solution result has been written in the first buffer at step 316. If this question is answered in the affirmative (Y), step 319 follows, asking whether no solution result has been written in the second buffer at step 316. If this question is answered in the affirmative (Y), then the word to be replaced at this position in the text may not be replaced by the replacement word, then the program returns to step 303. The word to be replaced and the replacement word vote alone correspond in notation, while the rest is disharmonious. With words like "like" in the English language and "regent" in the Dutch language, something like this can occur. Thus, in a sentence "it is raining" the word "regent" cannot be replaced by "driver".

If the question is answered in the negative (N) at step 318, then step 320 follows, asking whether at step 316 exactly one solution result has been written in the first buffer. If this is the case (Y), then step 321 follows. If this is not the case (N), then step 322 follows, where of each solution result the number of characteristics that it has in common with the word structure to be replaced is determined, after which step 323 the solution result with the largest number of common features is selected, and the program proceeds to step 321.

If the question is answered in the negative (N) at step 319, then step 324 follows, asking whether at step 317 exactly one solution result has been written in the second buffer. In the affirmative answer (Y), step 321 follows, and in the negative answer (N), said steps 322 and 323 follow in sequence, after which the program proceeds to step 321.

At step 321, the old word structure is replaced by the new word structure, which may or may not have been obtained by selection at steps 322 and 323. The pointer in the command field of the old word structure is adopted for the purpose of the command field of the new word structure. Then, at step 325, the constituent structure of the parent constituent is retrieved from the representation memory, and in the structure element field that combination is selected which has a pointer to the old word structure.

This pointer is replaced by one, which refers to the new word structure. The functional label is of course not changed. In the next step 326, a program portion for the called parent constituent is completed as described in steps 174 to 183 (see Fig. 15), adapting the characteristics and the error message field to the new situation.

Then, at step 327, it is checked whether there is still a higher level parent constituent. To this end, it is checked whether the command field of the current constituent is empty (NIL). If this question is answered negatively (N), step 328 follows, calling the higher level parent constituent from the representation memory, and then the program to step 326 returns to apply the associated program to that parent constituent. If the question is answered affirmatively (Y) at step 327, then a program as described at steps 158 to 173 (see Fig. 14) is executed at the next step 329. In this way, the sentence structure is corrected further if necessary.

Now that it is clear that the entire action has yielded results after step 301, in the next step 330 the old sentence structure can be replaced by the new one. The program then returns to step 303 in search of the next word to be replaced.

Thus, when replacing the word "device" in the entire text with "copiers", a phrase such as "The Device Standing There" will automatically be replaced by "The Copiers Standing There".

Table A

(ap (adj-inflected adj-not-inflected)) (np (definite indefinite neuter inneuter singl sing2 sing3 plul plu2 plu3 no-adj. adj.-inflected adj.-not-inflected)) (conj-np (definite indefinite neuter internal))

Table B

(article (np (det)) (pp (det np)) (s (det np)) (s-rel (det np)) (s-comp (det n))) (adj (ap (head)) ( np (head ap)) (s (head ap np) (head ap-adj)) (s-rel (head ap np) (head ap-adj)) (s-comp (head ap np) (head ap-adj )) (ap-adj (head))) (adv (s (head ap-adv)) (s-rel (head ap-adv)) (s-comp (head ap-adv)))) (advmod (ap ( mod ap)) (np (mod ap ap)) (s (mod ap ap np) (mod ap-adj)) (s-rel (mod ap ap npHmod ap-adj)) (s-comp (mod ap ap np ) (mod ap-adj))) (p-word (np (head pp)) (pp (head)) (s (head ppMvfin-particle)) (s-rel (head ppMvfin-particle)) (s-comp (head pp) (vfin-particle))) (c-word (s (comp s-comp))) (noun (np (head)) (pp (head np)) (s (head np)) (s- rel (head np)) (s-comp (head))) (pro-subst (np (head)) (pp (head np)) (s (head np)) (s-rel (head np)) (s -comp (head np))) (pro-rel (np (head np s-rel)))) (pro-adj (np (det)) (pp (det np)) (s (det np)) (s- rel (det np)) (s-comp (det np))) (verb (s (vfin-main)) (s-rel (vfin-main)) (s-comp (vfin-main))) (verb- intr. (s (Vfln-intr}) (s-rel (Vfin-intr)) (s -comp (Vfin-intr))) (interpunction (s (endmark)))

Table C

(np (det nmod-a) head) (pp 0 pobj) (ap (mod)) (ap-adj (mod) head) (ap-adv (mod) head) (s () fnp) (s-rel ( fnp) vfin-main) (s-comp (fnp) vfin-main) (conj-s (seq)) (conj-pp (seq)) (conj-ap (seq)) (conj-s-rel (seq) )

Table D

(ap (head (adj-inflected adj-not-inflected)) (amod (adj-Inflected adj-not-inflected))) (np (det (neuter inneuter singl sing2 sing3 plul plu2 plu3 definite indefinite)) (head (singl sing2 sing3 plul plu2 plu3 neuter inneuter)) (nmod-a (adj.-inflected no-adj. adj.-not-inflected)))

Table E

(s ((fnp fnp) (smod smod) (smod fnp) (fnp smod) (vfin-particle fnp) (vfin-particle) (fnp vfin-particle vfin-main fnp) (fnp vfin-particle fnp vfin-main fnp )) 0 ((vfin-main 1) (fnp 3) (Vffn-intr fnp 1))) (s-rel () () ((vfin-main 1) (fnp 3) (Vf ^ -intr fnp 1) )) (s-comp {) () ((vfin-main 1) (fnp SHVfin'Ïntr fnp 1))) (np ((head head)) {{det head) (nmod-a head) (head nmod- s) (det nmod-s)) ((det 1) (head 1) (nmod-a 1))) (pp ((head head) (head head pobj head)) 0 ((pobj 1)))

Table F

(np ((neuter inneuter) (singl sing2 sing3 plul plu2 plu3)) ((definite adj-inflected) (plu3 adj-inflected) (inneuter adj-inflected) (neuter indefinite adj-not-inflected)))

Table G

(np (conj-np conj) (pp pobj) (s fnp) (s-rel fnp) (s-comp fnp)) (conj-np (pp pobj) (s fnp) (s-rel fnp) (s- comp fnp)) (ap (ap amod) (np nmod-a) (s smod) (s-rel smod) (conj-ap conj) (s-comp smod)) (conj-ap (ap amod) (np nmod -a) (s-smod) (s-rel smod) (s-comp smod)) (ap-adj (s fnp) (s-rel fnp) (s-comp fnp)) (ap-adv (s smod) ( s-rel smod) (s-comp smod)) (pp (np nmod-p) (s smod) (s-rel smod) (conj-pp conj) (s-comp conj)) (conj-pp (np nmod -p) (s-smod) (s-rel smod) (s-comp smod)) (s (conj-s conj)) (s-comp (s fnp)) (s-rel (np nmod-s) (conj -s-rel conj)) (conj-s-rel (np nmod-s))

Table Η {(fnp vfin-main endmark) (subj)) ((fnp vfin-main smod endmark) (subj)) ((smod vfin-main fnp endmark) (subj)) ((smod vfin-main fnp smod endmark) (subj)) ((vfin-main fnp endmark) (obj)) ((vfin-main fnp smod endmark) (obj)) ((fnp vfin-main fnp endmark) (subj obj) (obj subj)) ((fnp vfin-main smod fnp endmark) (subj obj)) ((smod vfin-main fnp fnp endmark) (subj obj)) ((fnp vfin-main fnp smod endmark) (subj obj) (obj subj)) ((vfin- main fnp fnp endmark) (indobj obj)) {(vfin-main fnp smod fnp endmark) (indobj obj)) ((vfin-main fnp fnp smod endmark) (indobj obj)) {(vfin-main smod fnp fnp endmark) (indobj obj)) ((fnp vfin-main fnp smod smod endmark) (subj obj) (obj subj)) ((fnp vfin-main smod fnp smod endmark) (subj obj)); etc.

((fnp vfin-main fnp fnp endmark) (subj indobj obj) (indobj subj obj) (obj subj indobj)) ((fnp vfin-main smod fnp fnp endmark) (subj indobj obj)) ((smod vfin-main fnp fnp fnp endmark) (subj indobj obj)) ((fnp vfin-main fnp smod fnp endmark) (subj indobj obj) (indobj subj obj) (obj subj indobj)) ((fnp vfin-main fnp fnp smod endmark) (subj indobj obj) (indobj subj obj) (obj subj indobj)); etc ((fnp vfin-main) (subj)) ((fnp fnp vfin-main) (subj obj)) ((fnp fnp fnp vfin-main) ( subj indobj obj))

Table I

(s ((subj vfin-main) (sing3 sing2 singl plu3 plu2 plul)) {(subj) (nominative definite indefinite proper)) ((obj) (not-nominative definite indefinite proper)) ((indobj) (not-nominative definite indefinite proper))) (s-rel ((subj vfin-main) (sing3 sing2 singl plu3 plu2 plul)) ((subj-rel vfin-main) (sing3 plu3 singl sing2 plul piu2)) ((subj) (nominative definite indefinite proper)) ((obj) (not-nominative definite indefinite proper)) ((indobj) (not-nominative definite indefinite proper))) (s-comp ((subj vfin-main) (sing3 sing2 singl plu3 plu2 plul )) ((subj) (nominative definite indefinite proper)) ((obj) (not-nominative definite indefinite proper)) ((indobj) (not-nominative definite indefinite proper)))

Table K.

(np ((piu3 proper pro) (det) ()) ((sing3 definite) 0 (det)) ((definite indefinite) () (nmod-a nmod-s))

((definite indefinite ajd-inflected adj-not inflected) () (det))) Table L

(np (head det nmod-s nmod-a)) (ap-adj (head))

Claims (2)

1. Method for parsing and correcting a grammatically incorrect sentence in natural language, whereby the parse of this sentence in phrases to be described with functional indications takes place on the basis of word units, which are verbal categories and application-oriented categories lexicalised, characterized in that the method of the type described in the preamble is characterized by the following steps to be performed per word unit of the sentence: a. Determining the functional word category within the constituent per word unit and per constituent and / or within a newly created constituent, based on information about the verbal category of the word unit concerned and the category of the constituent; b. Describing for each constituent on the basis of information about the category of the constituent and the category of the constituent dominating this constituent a measure concerning the closure of the constituent, as well as the granting of a functional label, whether or not provisional, to be completed at that time. closing constituent; c. Testing the present constituent against syntax-based rules regarding the coherence of words and / or constituents within this constituent in at least one of the latter two steps, and, if necessary, revalue an expectation assigned to the sentence representation! ngs factor, as well as selecting any sentence representation whose expectation factor is above a certain threshold; and d. Selecting the grammatically incorrect Constituent within the sentence and then changing this Constituent based on rules based on syntax rules. Device for performing the method according to claim 1.