JPH0798702A - Document preparing device - Google Patents

Abstract

PURPOSE:To display the useful example sentences with preference by providing a storing means to store the control data for display of example sentences in relation to a cooccurrence word dictionary. CONSTITUTION:A ROM 2 stores the KANA (Japanese syllabary)/KANJI (Chinese character) basic word dictionary data 201, the additional word dictionary data 203, the 1st example dictionary data 205, etc. An example retrieval processing part 12 retrieves the cooccurrence word dictionary data 204, the data 205 and the 2nd example dictionary data 206 in relation to those word data stored in a homonym table 306. Then the part 12 stores the data on the example where the relevant word serves as a key into an example table 307. Then a following-word retrieval processing part 14 retrieves the word to be displayed next and its nomonyms based on the word data and the example data stored in both tables 306 and 307 respectively. Thus the display order or the presence/ absence of display is decided based on those control data when an example sentence is produced from a cooccurrence word dictionary 204.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a document processing device. In particular, the present application relates to a Japanese word processor (word processor) having a display function of example sentences.

[0002]

2. Description of the Related Art When performing kana-kanji conversion in a word processor, a user needs to select a homonym. However, some homophones are misleading, depending on the usage. In such cases, it is necessary to find out which word should be used.

Therefore, in some cases, when an example dictionary key is pressed after inputting a kana by romanization etc., a plurality of example sentences including homonyms corresponding to this kana input are displayed. It is known to create data for displaying this example from a co-occurrence word dictionary. The co-occurrence word dictionary is disclosed in Japanese Patent Laid-Open No. 1-229367 (G06F15 / 20) and the like. Further, the creation of example sentences from such a co-occurrence word dictionary is well known as shown in Japanese Patent Laid-Open No. 4-268945 (G06F15 / 20).

[0004]

[Problems to be Solved by the Invention] However, in this way,
When creating and displaying example sentences with the co-occurrence word dictionary,
Some words have many example sentences.
Therefore, it is inconvenient to display all the example sentences created by the co-occurrence word dictionary in the order of creation.

[0005]

A feature of the present invention is that, in a document creation apparatus that creates and displays example sentences using a co-occurrence word dictionary (204), the co-occurrence word dictionary (204) A storage means (205) for storing control data for displaying an example is provided.

[0006]

The feature of the present invention is that, when an example sentence is created by the co-occurrence word dictionary (204), the display order or the presence / absence of display is set by this control data.

[0007]

[Examples] For the sake of simplicity, a first example will be first described centering on the description of the display contents of the screen, and then a second example centering on the description of the internal operation will be described. (A) Description of the first embodiment. A first embodiment of the present invention will be described with reference to FIGS.

FIG. 1 shows the appearance of this Japanese word processor (word processor). In FIG. 1, (1) is an input unit, which comprises a keyboard. (1a) is a kana-kanji conversion key. (1b) is an example dictionary key. (1c) is a four-character idiom search key. (5) is an output unit, which is composed of a liquid crystal display screen. FIG. 2 is a diagram showing an operation at the time of displaying an example of this word processor.

The operation of the first embodiment will be described below with reference to FIGS. 1 and 2 and FIGS. 3 to 10 showing the contents of the display screen. First, the keyboard (1) is operated to display the reading by kana or romaji input as shown in FIG. In the case of Fig. 3, I entered "Koibito".
In addition, in FIG. 3, (K) is a cursor display, and (L) is an underline indicating that it is a target of kana-kanji conversion.

When the kana-kanji conversion key (1a) of the keyboard (1) is pressed, kana-kanji conversion is performed and "Meet my lover" is displayed as shown in FIG.

Next, when the example dictionary key (1b) is pressed, the operation is performed according to FIG. In other words, Kana-Kanji conversion has already been performed here. Since "Meet the lover" is composed of the bunsetsu "To the lover" and the bunsetsu "Meet", the information of the word "Meet" corresponding to the "Meet" of the last bunsetsu is extracted. This information is the word "meet" itself and the part of speech "verb" of this word.
Read "Au". Then, a plurality of homonyms are internally searched. Furthermore, the four-character idioms related to the plural homonyms are also searched to confirm the existence of these four-character idioms.

Next, a plurality of homonyms and their examples are displayed. At this time, if there are four-character idioms for the homonyms, those homonyms are enclosed by "★" and "★", and if there are no four-character idioms, they are enclosed by "[", "]". To display.

That is, the display is as shown in FIG. Incidentally, in FIG. 5, (5a) is an example display area. In this example display area (5a), three homonyms of the reading "Au" are displayed, and a maximum of three examples are displayed for each. A co-occurrence word dictionary is used to create this example sentence. The co-occurrence word dictionary (not shown) of this embodiment stores “breath”, “opinion”, “number”, “type”, ... As co-occurrence words of “fit”.

However, due to the control data indicating whether the example sentence is displayed or not, "the number matches" is not displayed. By the way, as can be seen from FIG. 5, there are related four-letter idioms in “meet”.

Here, when the user wants to display the four-letter idiom related to this "meet", the user moves the cursor to this "meet".
Move to the top and press the four-character idiom search key (1c). As a result, the four-character idiom and the meaning notation are displayed in the four-character idiom display area (5b) as shown in FIG.

In the above description of the operation, "meet the baby"
After inputting, the kana-kanji conversion key (1a) was pressed, and after converting to “meet my lover”, the example dictionary key (1b) was pressed. However, as you can see from the operation explanation of Fig. 2, even if you do not press the Kana-Kanji conversion key (1a), if you press the example dictionary key (1b), the Kana-Kanji conversion operation will be automatically performed and the same display will be displayed. .

In addition, after inputting "Match Koibito",
After pressing the Kana-Kanji conversion key (1a) to convert to "Meet my lover", and further pressing the Kana-Kanji conversion key (1a), the result is as shown in FIG. When the example dictionary key (1b) is pressed after converting "fit for a lover" in this way, the converted "fit" is given priority and displayed as shown in FIG. Also, as shown in Fig. 9, after entering "Kou", press the Kana-Kanji conversion key (1a),
If you press the example dictionary key (1b) after converting to "Beg", this converted "Beg" has priority and the same part of speech (verb)
Is given priority, so it is displayed as shown in FIG.

Further, as shown in FIG. 10, after inputting this "Kou", pressing the Kana-Kanji conversion key (1a) to convert it to "School" and then pressing the example dictionary key (1b) “School” is given priority, and the same part of speech (noun) is given priority, so that it is displayed as shown in FIG.

(B) Description of the second embodiment. A second embodiment of the present invention will be described with reference to FIGS. 11 to 35.

(B-1) Description of each part of the second embodiment. Figure 11
It is a block diagram of the word processor of this Example. (1) is an input unit including a keyboard. The input unit (1) is provided with various instruction keys such as a character key for inputting a kana character string by kana input or roman character input, a kana-kanji conversion key for instructing kana-kanji conversion, a cursor movement key, and an example dictionary key.

(2) is a read-only memory (ROM). This ROM (2) stores Kana-Kanji basic word dictionary data (201), ancillary word dictionary data (203), first example dictionary data (205), etc. which are necessary when performing Kana-Kanji conversion and example reference. (3) is a readable / writable memory (RAM). RAM (3) is a kana input buffer (301) and a kanji output buffer (30
2), the example table (307) and the like are stored.

(4) is a control unit. The kana character string and the instruction input from the input unit (1) are given to the control unit (4). The control unit (4) controls the data exchange of each unit of the device according to the given instruction and outputs the input character string to the output unit (5) including an LCD display or the like. (6) is a kana-han control unit that controls kana-kanji conversion.
If the given input is a kana character string, the kana-han control unit (6) stores a reading code string corresponding to the kana character string in the kana input buffer (301) in the RAM (3). When the kana-kana mixed character string is determined as a result of kana-kanji conversion, the kana input buffer (301) is initialized. If the given input is a kana-kanji conversion instruction, the word candidate creating unit (7), the phrase candidate creating unit (8), and the output candidate creating unit (9) are sequentially activated.

The word candidate creating unit (7) is a kana input buffer.
The reading code string stored in (301) is sequentially matched with the reading code strings of the Kana-Kanji basic word dictionary data (201) and the Kana-Kana Katakana dictionary data (202) in the ROM (2). The data is stored in the word candidate table (304) in the RAM (3) such as the part-of-speech and the appearance frequency of the word having the matching reading code string. At this time, adjunct word processing is performed using the adjunct word dictionary data (203) in the ROM (2) and stored in the word candidate table (304).

The phrase candidate creating unit (8) is a word candidate table.
From the word data stored in (304) and the co-occurrence word dictionary data (204) in ROM (2), the reading code string stored in the kana input buffer (301) is punctured, and the punctuation data is punctured. Store in the candidate table (305). Output candidate creation unit (9)
Uses the phrase segmentation data stored in the phrase candidate table (305) to store the word notation code, word management data, etc. in the RAM (3).
It is stored in the kanji output buffer (302).

(10) is an example reference control unit. The example reference control unit (10) includes a homophone search processing unit (11), an example search processing unit (12), a four-character idiom search processing unit (13), and a homophone output processing unit (1).
5) Start the example output processing unit (16) and the four-character idiom output processing unit (17). In addition, the example reference control unit (10) responds to the instruction from the input unit (1) with the homophone output buffer (30) in the RAM (3).
9), example output buffer (310), four-character idiom output buffer (31
1), Transfer the data such as notation codes necessary for display stored in the Kanji output buffer (302) to the display buffer (303),
Output to the output section (5). Alternatively, the next word search processing unit (1
4), Activate the selected word output unit (18).

The homophone search processing section (11) has a notation code string of words stored in the kana input buffer (301) and kanji output buffer (302), kana-kanji basic word dictionary data (201) and kana. Matching with the Chinese Katakana dictionary data (202) is performed to determine whether the word is a homophone, and the word data that is a homophone is stored in the homophone table (306).

The example search processing section (12) uses the homophone table (3
For each word data stored in (06), search the co-occurrence word dictionary data (204), the first example dictionary data (205), the second example dictionary data (206), and use the corresponding word as a key. The data of the present example is stored in the example table (307). The next word search processing unit (14) searches for the word to be displayed next and its homonyms from the word data and the example data stored in the homonym table (306) and the example table (307). For example, when the word data is "breath" and the example data indicates "breath is good", the example data "breath is good" indicates that the word data is "breath" and the word data is "fit (u)". This is an example. The remaining word data “U” and its homophone data are generated and output to the homophone table (306).

The homophone output processing section (15) is a homophone table.
For each word data stored in (306), search the Kana-Kanji basic word dictionary data (201) and the Kana-Kana Katakana dictionary data (202), generate the notation code of the corresponding word, and Stored in the output buffer (309). The example output processing unit (16), for each example data stored in the example table (307), the Kana-Kan basic word dictionary data (201), the Kana-Kan Katakana dictionary data (202), and the co-occurrence word dictionary. Data (204), first example dictionary data (205), second example dictionary data (2
06), example priority table (208), example annex word table (209),
The inflection word display data (210) is searched, the notation code of the corresponding example is generated, and stored in the example output buffer (310).

The four-character idiom search processing unit (17) searches the four-character idiom dictionary data (207) for each word data stored in the homophone table (306), and the corresponding word is a key. The example data is stored in the four-character idiom table (308). Further, the four-character idiom output processing unit (17), regarding each four-character idiom data stored in the four-character idiom table (308),
Kana-han basic word dictionary data (201), four-character idiom dictionary data (2
07), generate the corresponding notation code of the four-character idiom and the meaning notation code of the four-character idiom, and output the four-character idiom output buffer (3
Store in 09).

The selected word output processing unit (18) uses the word data stored in the homophone table (306), the notation code stored in the Kanji output buffer (302) which is the kana-Kanji conversion result, the word management data, etc. A new notation code for displaying the designated word, word management data, etc. are newly generated and output to the Kanji output buffer (302).

(B-2) Description of the operation of the second embodiment. The operation of this word processor will be described. The kana-kanji conversion function will be described below. The example display will be described later in (B-2-2).

(B-2-1) Explanation of kana-kanji conversion operation. When the kana character string "Koibitoiai" is sequentially input from the input section (1), the control section (4) activates the kana-han control section (6) and converts the kana character into the kana input buffer (301). The corresponding reading code is stored while incrementing the writing position as shown in FIG.

When a kana-kanji conversion instruction is input from the kana-kanji conversion key of the input section (1), the kana-kanji control section (6) displays a reading code string stored in the kana input buffer (301) followed by a separator indicating the end of input. The code "0" is written and the word candidate creation unit (7) is activated. The word candidate creation unit (7) uses the reading code string “Koibittoai” stored in the input buffer (301).
And the kana-hanka basic word dictionary data (201) shown in FIG. 13 and the kana-hanka katakana dictionary data (202) shown in FIG.

This comparison judgment is performed from the 0th array of the reading code of the words in the Kana-Kanji basic word dictionary data (201) and the Kana-Kana Katakana dictionary data (202) and the input buffer (301). "Compare with Koibito" in, then compare with "Meet with Koibito" from the first array ,. ． , And comparison with “Au” from the 5th sequence. The kana-han basic word dictionary data (201) and the kana-han katakana dictionary data (202) include a reading code string corresponding to the reading of the word, a notation code string corresponding to the notation of the word, and the frequency of occurrence of the word. , With parts of speech. For reading and notation of words, only stems excluding inflectional endings are used. For example, "Meet" means "reading of words: a, notation: meeting."
Is stored.

The process until the word candidate "lover" is stored in the word candidate table (304) will be described below. In the comparison with the array of reading code strings stored in the kana input buffer (301), "meeting with Koibito" from the 0th,
Compare with Kana-Kanji basic word dictionary data (201).

When the reading code “Koibito” of the word number 10191 in FIG. 13 is compared with the reading code string “Koibito” stored in the Kana input buffer (301), the reading of the word is the input character. Fully contained in the column. Further, since the part of speech of the word with the word number 10191 is a noun and has no inflectional ending, the word candidate table (30
While storing the word candidate data in 4), search the adjunct word data of the adjunct word dictionary data (203) as shown in FIG. 15,
The reading code of the adjunct word "ni" following "Koibito" in the Kana input buffer (301) is the Kana-Kanji basic word dictionary data.
It is verified whether the word "lover" read from (201) can be continuously connected.

That is, the auxiliary word dictionary data (2
The ancillary word data that can be connected to the noun in 03) is compared with the reading code string “Ai” that follows the above word candidate. As shown in the adjunct dictionary data (203) in Fig. 15, the adjunct word "ni" is attached to the noun.
16A, the word candidate data with the attached word is stored in the word candidate table (304) as in array (8) in FIG. 16 (A). Next, the Kana-Kana Katakana dictionary data (20
Do the same for 2), but in this case, there is no matching data.

The starting point in the word candidate table (304) of FIG. 16 is the starting position of the reading of the word candidate represented by the array number of the kana input buffer (301). In addition, the end point represents the end position of reading the word candidate by the array element number of the kana input buffer (301). The part-of-speech and frequency correspond to the appearance frequency and part-of-speech data in the Kana-Kan basic word dictionary data (201) and the Kana-Kan Katakana dictionary data (202). The adjunct word length is the length of the adjunct word portion of the word candidates. The attached word number is grammatical connection information. The word number is a number indicating the number of the word from the beginning of the dictionary in the Kana-Kan basic word dictionary data (201) and the Kana-Kan Katakana dictionary data (202). However, Kana-Kanji basic word dictionary data (201) and Kana-Kana Katakana dictionary data (20
In order to distinguish which is 2), the word number in the Kana-Kana Katakana dictionary data (202) is a constant 300 as shown in Fig. 14.
It starts from 01.

Next, the word candidate "Meet" is the word candidate table.
The process until it is stored in (304) will be described. Similar to the above, in comparison with “Au” from the fifth array of reading code strings in the input buffer (301), the Kana-Kanji basic word dictionary data (2
01) and Kana-Kana Katakana dictionary data (202) are compared sequentially.

When the reading code “A” of the word with the word number 1 shown in FIG. 13 is compared with the reading code string “Au” of the input character string, the reading of the word is completely included in the input character string. The part of speech of the word "Kai" with word number 1 has an inflection ending in 5 lines, so the adjunct word dictionary data (203) is searched to test whether or not the adjunct word can be continuously connected to the word. . The adjunct word data that can be connected to the adjunct word dictionary data (203) shown in Fig. 15 that can be used in 5 rows is compared with the kana character string "u" that continues to the above word. Since it is not possible to connect to the part-of-speech utilized in the fifth row, the word candidate data with the attached word is not stored in the word candidate table (304).

In the comparison with the next Kana-Kanji basic word dictionary data (201) with word number 2 "Go", both the comparison with the input character string and the adjunct connection test are OK, and the array of FIG. 16 (A) is obtained. It is stored in the word candidate table as shown in (14). Next word number 3
Similarly, "kai" is OK for both the comparison with the input character string and the adjunct connection test.

The word candidates stored in this way and the start point, end point,
If data that matches the part-of-speech, accessory word length, and accessory word number already exists in the word candidate table (304), add word number 3 to the word number data of the matching data as shown in Fig. 16 (B). I do. Finally, a word candidate table (304) as shown in FIG. 16 (C) is created. Kana-han basic word dictionary data (201),
When the comparison and determination with the Kana-Kana Katakana dictionary data (202) and the storage of the word candidate data in the word candidate table (304) are all completed, the phrase candidate creating unit (8) is activated.

The phrase candidate creating unit (8) is a word candidate table.
The kana character string stored in the kana input buffer (301) is segmented based on the word candidate data stored in (304). First, the word candidates are combined according to the starting point data and the ending point data of the word candidates, and “Koibitoni / Au” and “Koibito / Ai” are the segmentation candidates. Further, a score (evaluation value) is given to a plurality of punctuation candidates according to the reading length and frequency of each word candidate, and the priority of the punctuation candidates to be output is determined.

FIG. 17 shows a phrase candidate table, and the numerical values stored in the phrase 1, the phrase 2, etc. indicate the arrangement positions of the word candidate table (304) in FIG. 16 (C). The average phrase length is the total reading length of the combined word candidates divided by the number of combined word candidates. The average frequency is the sum of frequencies of combined word candidates divided by the number of word candidates. The evaluation value is obtained by adding this numerical value.

In the case of "Koibitoni / Meet", the average candidate length is (5 + 2) /2=3.5 and the average frequency is (8 + 12) / 2 = 10. The evaluation value is a value obtained by adding these, and is 13.5.
When the storage of the phrase candidate data in the phrase candidate table (305) is completed, the output candidate creation unit (9) is activated. The output candidate creating unit (9) selects the phrase candidate “Koibitoni / Au” (the phrase 1: 8, the phrase, which has the largest evaluation value from the phrase candidates stored in the phrase candidate table (305) shown in FIG. 2:14) selects it as an output candidate.

FIG. 18 shows a conceptual diagram of the co-occurrence word dictionary data (204) used to select a word to be output from the word candidates “Koibitoni” and “Au” of each clause. In FIG. 18, word numbers are stored. In FIG. 18, the letters corresponding to the word numbers are shown for the sake of simplicity. Figure
Data for a set of word A and word B in 18 and its word A
And a word form that represents the shape of the sentence formed by the word B. Word A,
The word number is stored in the data of word B.

First, the word candidate table (304) shown in FIG. 16 is arranged based on the word candidate number (8) corresponding to "Koibitoni".
The word number 10191 is obtained from the (8) th position. Then, based on the word candidate number (14) corresponding to “Au”, the word numbers 2, 3 and 4 are obtained from the (14) th array of the word candidate table (304) of FIG.
Then, the combination of these word numbers and the co-occurrence word dictionary data (204) are compared. {10191: 2}, {10191: 3}, {10191:
Out of 4}, "# 3" meeting (u) "of the co-occurrence word dictionary data (204): # 10
191 For the set of {10191: 3} words that match “lover”, the sentence shape and co-occurrence word dictionary data (20
Compare whether the word form of 4) matches.

When they match, priority is given to the output of these words. In this case, the relationship between the word “lover” and the word “meet” matches the connection of the word form data of the co-occurrence word dictionary data (204) “B to A to” and the particle “ni”. And the word "meet" are given priority, and the notation code and word management data are output to the Kanji output buffer (302). This word management data consists of the number of output phrases, the number of input kana characters corresponding to each phrase, the number of Kanji characters, and the number of adjunct words.

As shown in FIG. 19, "Meet a lover" is stored in the Kanji output buffer (302). The number of bunsetsu is "2" because the bunsetsu are "Koibitoni" and "Au". In addition, the number of kana characters in the first bunsetsu is 5, "Koibitoni", the number of kanji characters in the first bunsetsu is 3, "koibito ni", and the number of adjunct words in the first bunsetsu is 1, "ni". In the second bunsetsu, the number of kana characters "2" is stored, the number of kanji characters is "meeting" 2, and the number of adjunct words is "1".

When the storage in the Kanji output buffer (302) is completed, the control is returned to the control unit (4) to pass the data of the Kanji output buffer (302) to the output unit (5) for display.

(B-2-2) Explanation of operation of example display. here,
When the example dictionary key of the input unit (1) is input, the control unit (4)
Activates the example reference control unit (10).

The example reference control unit (10) is a homophone search processing unit.
(11), the example search processing unit (12), and the four-character idiom search processing unit (13) are activated in sequence. The homophone search processing section (11) obtains the target word of the example reference and its homophone data from the data stored in the Kanji output buffer (302) and the kana input buffer (301).
In this embodiment, the end of the bunsetsu is the target bunsetsu, but it may be the first bunsetsu.

In this process, first, the number of homophones in the homophone word table (306) as shown in FIG. 20 (A) is initialized. Then, the head position in each buffer of the kana code and the notation code, which is the reading of the target word, is obtained. In this case, the target word from the phrase number 2 stored in the Kanji output buffer (302) is “meet” in the second phrase. The starting position of the kana code in the kana input buffer (301) and the starting position of the notation code in the kanji output buffer (302) are respectively the kana character number data (5) of the first clause of the kanji output buffer (302) to the kana input buffer ( It is the fifth of the array of (301), and it is from the number of Kanji characters 3 to the array of the Kanji code buffer (302).
Third. The reading length of the target word is 2, and the kanji length is 2.

Using the word reading "Au", the Kana-Kanji basic word dictionary data (201) and the Kana-Kana Katakana dictionary data (20
2) Search for "Meet" the notation of the word with the same reading code
Compare with. As shown in FIG. 13, only the stem portion of the word is stored in the Kana-Kan dictionary (201), so no matching is performed.

Then, the reading code string and the last code of the notation code string are omitted from the reading "Au" and the notation "Meet". However, if it exceeds the adjunct word length, no search is performed. In other words, the search is made by reading "a" and "kai". As a result, the word number 3 “Meeting [wa 5 lines use]” is obtained. In this way, when the adjunct word portion is omitted and the search is performed, it is checked whether or not the adjunct word portion "u" can be connected using the adjunct word dictionary data (203) in FIG.

In this example, since "U" can be connected to use 5 rows of words, the check is true, and the part of speech and the word number are stored in the homophone table (306) as shown in FIG. 20 (B). . Further, it is checked whether or not this part of speech is the target of the example sentence. As a result of this check, if the part-of-speech is not likely to be included in the example sentence, the reading code string and the last code of the notation code string to be searched within the range of the number of adjunct words are omitted, and the Kana-Kanji basic word dictionary data (201) Tokana / Kana Katakana dictionary data (202) is searched again.

As a result of this check, if the part of speech is likely to be included in the example sentence, the homonym is searched.
To search for a homophone, the kana-hankanji basic word dictionary data (201) and the kana-hankana katakana dictionary data (202) are searched using the word reading “Au”. As shown in FIG. 13, since only the stem portion of the word is stored in the kana-han dictionary, there is no data matching “Au”.

Next, a search is made by reading "Au" without the last code. However, if it exceeds the adjunct word length, no search is performed. That is, the search is performed by reading "a". As a result, the word number "open" [use 5 rows] is obtained. In this way, when searching with the adjunct word part omitted, check whether the adjunct word "U" can be connected.
This is done using 15 accessory word dictionary data (203).

In this example, since "U" is not connectable to the use of 5 rows of lines, the check is false and the Kana-Kan basic word dictionary data (201) and the Kana-Kan Katakana dictionary data (202) are used. Continue searching. You can get the word number 2 "Uu [5 lines in 5 lines]". Since the adjunct word "U" can be connected, the check is true. Further, since the part of speech is the same as the part of speech of the homonym table and the word number 2 is not already stored in the homonym table (306), the word number 2 is stored and the number of homonyms is incremented by one. At this time, if it is different from the part of speech in the homophone table, the word number is stored in a temporary buffer (not shown).

This is the basic word dictionary data for Kana-han (201)
This process is repeated until there is no data that corresponds to the Katakana dictionary data for Tokana and Han (202). Finally, the word number stored in the temporary buffer (not shown) is stored following the word number already stored in the homophone table. Also at this time, the word number to be stored is stored only if it is not already stored in the homophone table (306).

Further, the number of homophones is incremented by the number of stored word numbers. A homophone word table (306) is created as shown in FIG. Then, the example search processing unit (12) is activated. First, the example search processing unit (12) initializes the example table (307) with constants such as END data and FFFF (H),
Further, as shown in FIG. 23 (A), the word numbers 3, 2, and 4 stored in the homophone table (306) are sequentially stored in the word numbers of the example table (307).

The first example dictionary data (205) and the second example dictionary data (206) are searched for these word numbers. Figure 21
A conceptual diagram of the first example dictionary data (205) is shown in FIG. The first example dictionary data (205) corresponds to each data of the co-occurrence word dictionary data (204). The data value 0 of the first example dictionary data (205) indicates that the corresponding co-occurrence word dictionary data (204) is not used for example display.

FIG. 22 shows a conceptual diagram of the second example dictionary data (206). The second example dictionary data (206) includes a notation code string of an example sentence and a keyword for searching. The keyword stores the word number of the keyword. For word number 3, words in the co-occurrence word dictionary data (204)
The word number data of A and the word number data of word B are searched, and the sequence number of the co-occurrence word dictionary data (204) is 105, 106, 107.
Is obtained.

First of these word numbers 105, 106, 107
It is checked whether the data value of the example dictionary data (205) is 0, that is, whether it is not used for the example display, and the one used for the example display is the sequence number of the co-occurrence word dictionary data (204).
It is stored in the example table (307) like 3 (B). Word number 2
In the case of, the word number data of word A and the word number data of word B of the co-occurrence word dictionary data (204) are searched, and 77,78,79,80 are obtained with the sequence number of the co-occurrence word dictionary data (204). To be

First of these word numbers 77, 78, 79, 80
It is checked whether the data value of the example dictionary data (205) is 0, that is, whether it is not used for the example display, and the one used for the example display is the sequence number of the co-occurrence word dictionary data (204).
It is stored in the example table (307) like 3 (B). In this case, as shown in FIG. 21, since the data value of the first example dictionary data (205) corresponding to the word number 79 is 0, the example table
It is not stored in (307).

Next, it is searched whether or not the keyword of the second example dictionary data (206) has the word number 2, and the matching second
The array element numbers 124 and 125 of the example dictionary data (206) are obtained. A constant is added to distinguish from the sequence number of the co-occurrence word dictionary data (204). This constant may be larger than the maximum array element number of the co-occurrence word dictionary data (204). In this example, 30000 is used as this constant. Therefore, the above SEQ ID NO: 30124
And 30125, as shown in the example table (3
Store in 07).

Similarly for the word number 4, FIG.
An example table (307) like this is created. Then, the four-character idiom search processing unit (13) is activated. The four-character idiom search processing unit (13) uses the four-character idiom table (308) to set END data and FFFF.
Initialize with a constant such as (H), and then use the word numbers 3, 2, and 4 stored in the homophone table (306) as the word numbers in the four-character idiom table (308) in order as shown in FIG. 24 (A). Store. The four-character idiom dictionary data (207) is searched for these word numbers 3, 2, and 4.

FIG. 25 shows a conceptual diagram of the four-character idiom dictionary data (207). The four-character idiom dictionary data (207) includes a word number of the four-character idiom, a meaning notation code string of the four-character idiom, and a keyword for searching. The keyword stores the word number of the keyword. First, search for word number 3 and match it with the keyword "Chiaki Aichi". The array number of the matched four-character idiom dictionary data (207) is stored in the four-character idiom table (308). Subsequently, the four-character idiom dictionary data (207) is searched for a word number 2 in the keyword, but in this case, no matching is performed. Then, the word number 4 is searched, and a four-character idiom table is created as shown in FIG. 24 (B).

As described above, the homonym table (306), the example table (307), and the four-character table are obtained by the homophone search processing section (11), the example-search processing section (12), and the four-character idiom search processing section (13). When the phrase table (308) is created, the example reference control unit (10)
In order to convert each into a notation code, the homophone output processing unit (15) and the example output processing unit (16) are activated. First, the example reference control unit (10) sequentially reads word numbers from the homonym table (306).

The first data of the word number is the word number 3, and this word number is sent to the homophone output processing section (15). The homophone output processing unit (15) generates and outputs the word notation data “meet” based on this word number. For the word numbers 2 and 4, the notation code is generated in the same manner, and "match" and "encounter" are shown in Fig. 26.
They are sequentially stored like the homophone output buffer (309).

In this way, the example reference control unit (10) sequentially stores the generated data in the homophone output processing unit (15) for each word. Details of the homophone output processing unit (15) will be described below. The homophone output processing unit (15) stores the kana-kanji conversion basic word dictionary data (201) or kana-kanji conversion katakana dictionary data (202) corresponding to the word number in order to convert the word number into a notation code. The notation code of the stem part of the existing word is read.

"Kai" is read from the notation data of the word number 3 stored in the homophone table (306), and the inflection word "u" is read from the part-of-speech data and the inflection word display data, and the generated inscription data "meet" Output. In addition, if there are multiple parts of speech of a word stored in the Kana-Kanji conversion basic word dictionary data (201) or the Kana-Kanji conversion Katakana dictionary data (202), the part-of-speech data stored in the homophone table (306). Matches or performs matching, and the matched part of speech is given the highest priority. Other parts of speech are stored in the Kana-Kanji conversion basic word dictionary data (201) or the Kana-Kanji conversion Katakana dictionary data (202) in order, but the priority for each part of speech is set separately and determined. The order may be good or good.

As shown in FIG. 29, the notation code stored in the Kana-Kanji conversion basic word dictionary data (201) or the Kana-Kanji conversion Katakana language dictionary data (202) as described above is used based on the part-of-speech data having the highest priority. A notation code to which the inflection word notation code is added is generated from the word notation data. Next, if there is a part of speech to be processed, the figure is based on this part of speech.
The conjugation word data is added by the 29 conjugation word notation data, but it is verified that the generated notation code does not match the already generated notation code, and the middle point notation code “•” is added, and after this The notation code generated in the same manner as above is added.

If it matches the one stored in the output buffer, the part of speech to be processed next is processed. When this process is completed, the notation code is output when all the parts of speech of the words stored in the Kana-Kanji conversion basic word dictionary data (201) or the Kana-Kanji conversion Katakana dictionary data (202) are completed. The processing when there are a plurality of parts of speech of this word will be described.

Like the part-of-speech of word number 16 "love" stored in the Kana-Kanji conversion basic word dictionary data (201), "noun"
Homophone table (306) with multiple "suffixes" and "sahen nouns"
The part-of-speech data of "is a sahen noun" will be described. Kana-Kanji conversion basic word dictionary data (201) stored in the homophone output buffer "love" from the word notation data, stored in the homophone table (306), and for Kana-Kanji conversion “Sahen noun” also in the basic word dictionary data (201) is processed with the highest priority, and “do” from the inflection word notation data of FIG. 29 is additionally stored in the homophone output buffer (309).

Next, since there is no data to add the part-of-speech "noun" to be processed, the data to be stored in the homophone output buffer (309) is "love", and the homophone output buffer has already been output.
Since it is not the same as the data "I love you" stored in (309), it is additionally stored in the homophone output buffer (309).
Next, there is no data to add the part-of-speech “suffix” to be processed, the data to be stored in the homophone output buffer is “love”, and the data stored in the homophone output buffer (309) is “love”. Since the same one has already been stored as compared with "love", the notation code is not stored in the homophone output buffer (309).

With this, the processing is completed for all parts of speech of the word "love", the notation code stored in the homophone output table becomes "love, love", and this is output. Homophone output section
When the processing of (15) ends, the example output processing unit (16) is activated. In this example output process (16), the example table (307)
A notation code is generated based on the example numbers stored in each word and the data is stored in the example output buffer (310) for each word as shown in FIG.

That is, according to the example table (307) of FIG. 23, the first example of the word to be displayed first is the example number 105, and this example number is sent to the example output processing section. The example output processing unit generates and outputs the notation code “meet my lover” based on the example number 105. The output notation code is stored in the example output buffer (310) for each example of each word as shown in FIG. This process is performed for all the example numbers stored in the example table (307).

The example output processing section (16) will be described in detail below. In addition, this explanation will be made on the operation of the second displayed word. The first example of the second word to be displayed is the example number 77 according to the example table (307) of FIG. When the example output processing unit (16) receives the example number 77 from the example reference control unit (10), the example output processing unit (16) determines whether the example is the first example dictionary data (205) or the second example dictionary data (206) according to the example number. To judge. That is, if the example number is less than 30000, it is the example of the first example dictionary data (205), and if it is 30000 or more, it is the example of the second example dictionary data 206.

Since the example number 77 is less than 30,000, it is the first
An example notation code is generated based on the example dictionary data (205). Hereinafter, generation of the notation code of the example based on the first example dictionary data (205) will be described. Example output processing unit
(16) is 77 of the co-occurrence word dictionary data (204) from example number 77.
The second data is read.

The co-occurrence word dictionary (204) consists of a set of word numbers and phrase form data.
The word number 2 that represents ((u)) and the word number 1142 that represents the word "breath",
Data of the phrase form "B does A do" is obtained. The first example dictionary data (205) is associated with the co-occurrence word dictionary data (204) and represents which of the phrase form data in the corresponding co-occurrence dictionary data is used for example display. In the example priority table (208) as shown in FIG. 30, the word form data is arranged in the priority order.

That is, the first example dictionary data (205) is 0
When, the example of the corresponding co-occurrence dictionary data (204) is not displayed. A value of 1 indicates word / phrase form data having the first priority among the word / phrase form data of the co-occurrence dictionary data arranged in the priority order of the example priority table. In the case of example number 77, the value of the first example dictionary data (205) is 1 as shown in FIG. 21, and the corresponding co-occurrence word dictionary (20
Since the phrase form data in 4) is “B does A”, the phrase form data used for the example display is “B does A”.

By the way, the example attached word table (20
The order / inverse data of 9) indicates the order of words A and B. That is, if the form data “A does B”, the order is “0”, and if “B does A”, the order is “1”. Next, the example attached word table in Figure 31
Since the order / reverse data indicating the order of the words A and B in the phrase form data “B does A” of (209) is 1, which indicates the reverse, the word number 1142 of the word B in the co-occurrence word dictionary (204) Is the notation code.

The notation code "breath" of the word number 1142 is obtained from the Kana-Kanji conversion basic word dictionary data (201). Next, add the notation code "ga" from the auxiliary word data of the example auxiliary word table (209), and then add the notation code "Go" of word number 2 obtained from the basic word dictionary data for Kana-Kanji conversion (201). Add.

Further, the inflection word "u" of the part-of-speech of the word number 2 "wa row 5 dan inflection" obtained from the inflection word notation data of FIG. 29 is added to generate the example notation code "breath fit". ,Output.
Also, the second example dictionary data (206) such as word number 30124
When obtaining the notation code of the example based on, obtain 124 by subtracting 30000 from the word number, and from this value the 124th example sentence notation code of the second example dictionary data (206) `` Water does not fit ''
Is output.

When the storage of data in the homophone output buffer (309) of FIG. 26 and the example output buffer (310) of FIG. 27 is completed as described above, the example reference control unit (10) displays.
When the homophone is displayed, it is checked whether or not a four-character idiom exists for the word using the data of the four-character idiom table (308). If there are four-letter idioms, they are displayed together in the same phoneme with “★” and “★”. If there are no four-letter idioms, they are displayed together in “[”, “]”.

The homophone output buffer (30
Use the data from 9). Following the display of this homophone, three examples corresponding to that word are displayed. When there are four or more examples, "○" is displayed at the beginning of the line that displays three examples, indicating that the examples could not be displayed on one screen. A description will be omitted of the means for displaying the examples that could not be completely displayed by operating the display switching key such as the example list.

When the display of the first homophone and the example is completed, the homophone and the example are displayed in the same manner for the second homophone and the third homophone, and as shown in FIG. A message like this is displayed and a key input waiting state is entered. Further, the cursor can be moved to the homophone part and the example part in response to the input of the cursor key, and the cursor control is performed by associating the cursor position with the homophone output buffer and the example output buffer.
That is, from the cursor position, the classification as to whether it is a homophone or an example and the word number of the homophone or the example number of the example can be obtained.

(B-2-3) Four-character idiom display processing. Next, the four-character idiom search will be described using a specific example. As shown in Fig. 32 (A), when the cursor is at the homonym "Meet" enclosed by "★" and "★", if you enter the four-character idiom search key, the example reference control unit (10) will move the cursor. Word number 2 obtained from position
Is sent to the four-character idiom output processing unit (17).

The four-character idiom output processing unit (17) generates and outputs the word notation data “One day thousand autumn” and the meaning notation data “One day is felt like a thousand years” from the word number. The example reference control unit (10) stores the output four-character idiom notation data and meaning notation data in the four-character idiom output buffer (311) and displays the four-character idiom and meaning notation as shown in Fig. 33. Area (5
Control to display in b).

The four-character idiom output processing unit (17) searches the four-character idiom table (308) for word number data to obtain the four-character idiom number 99 corresponding to the word number 2. Four-character idiom dictionary data (2
07) based on the 99th word number 1528 in the Kana-Kanji basic word dictionary data (201)
To get In addition, the semantic notation data “a day feels like a millennium ...” is obtained from the 99th meaning notation data of the four-character idiom dictionary data (207), and these are output.

(B-2-4) Adjunct word processing at the time of writing. Next, the word writing of the homophone will be described using a specific example. As shown in FIG. 32 (B), when the enter key is pressed when the cursor is located at the homophone “fit”, the example reference control unit (10) selects the word number 2 obtained from the cursor position as the selected word output processing unit ( Send to 18).

The selected word output processing section (18) synthesizes the kana-kanji converted auxiliary word and outputs it to generate and output a notation code. The output notation code is converted to kana-kanji and replaced with the displayed character string for display. In this selected word output processing unit (18), the word number is stored in the kana-kanji conversion basic word dictionary data (201) or the kana-kanji conversion katakana dictionary data (202) for converting the word number into the notation code. The notation code of the stem part of the word is read. Get the notation code "Go" from the word number 2. Kanji output buffer (302) 2nd bunsetsu word number 1
Based on the above, the notation code “U” of the attached word portion extracted from the end stored in the notation code buffer is added, and the notation code “fit” is output.

(B-2-5) Next word search process. Next, the next word search process will be described using a specific example. When the cursor is moved and the cursor is on the example “Breathe” as shown in FIG. 32 (C) and the next word search instruction key is entered, the example reference control unit (10) displays the example number obtained from the cursor position. 77 and word number 2 are sent to the next word search processing unit (14).

The next word search processor (14) has an example number of 3000.
If it is less than 0, the first example dictionary data (205) is searched, and if it is 30,000 or more, the second example dictionary data (206) is searched. Since the sent example number is 77, the first example dictionary (205) is searched. As shown in Fig. 21, the first example dictionary (205) is a co-occurrence word dictionary.
It is associated with (204), and the 77th word group data “# 2, # 1142” of the co-occurrence word dictionary (204) can be obtained from the example number 77.

From this data and the sent word number 2, the word number 1142 to be searched next can be obtained.
Next, the word notation code "breath" and the word reading code "iki" stored in the kana-kanji conversion basic word dictionary data (201) corresponding to the word number 1142 are obtained. Next, FIG. 34 (A)
Initialize the number of homophones in the homophone table (306) as shown in FIG.

Using the word reading "iki", the Kana-Kanji basic word dictionary data (201) and the Kana-Kana Katakana dictionary data (20
Search 2) and compare the notation of the matched word with "breath". Thereafter, matching is performed in the same manner as the homonym processing unit (11). Figure 34
As in (B), word number 1142 "breath", word number 1142 "spirit",
The word number 1151 "Abandoned" is obtained as a homonym and stored in the homonym table (306).

Thereafter, similar to the above processing, the example reference control unit (10) includes an example reference search unit (11) and a four-character idiom search processing unit.
(12), the homophone output processing unit (15), and the example output processing unit (16) are respectively activated to perform the display shown in FIG.

In the first and second embodiments, the control data is the data for determining whether to display. However, the present application is not limited to this. That is, in this embodiment, when the control data is "0", the example sentence is not displayed. However, the example sentence may be displayed even when the control data is “0”. However, the display order is such that the control data comes after the example sentence with the control data "1".

Further, in the present embodiment, all the example sentences are created from the co-occurrence word dictionary, but the present invention is not limited to this.

Further, in the present embodiment, the presence or absence of the display is determined only by the control data, but the present invention is not limited to this.

[0102]

According to the present invention, it is possible to preferentially display example sentences which are considered to be useful.

[Brief description of drawings]

FIG. 1 is a diagram showing an appearance of a first embodiment of the present invention.

FIG. 2 is a flowchart showing the operation of the first embodiment.

FIG. 3 is a diagram for explaining screen contents of the first embodiment.

FIG. 4 is a diagram for explaining the screen contents of the first embodiment.

FIG. 5 is a diagram for explaining screen contents of the first embodiment.

FIG. 6 is a diagram for explaining screen contents of the first embodiment.

FIG. 7 is a diagram for explaining the screen contents of the first embodiment.

FIG. 8 is a diagram for explaining the screen contents of the first embodiment.

FIG. 9 is a diagram for explaining screen contents of the first embodiment.

FIG. 10 is a diagram for explaining screen contents of the first embodiment.

FIG. 11 is a block diagram of a second embodiment of the present invention.

FIG. 12 is a diagram for explaining a kana input buffer according to the second embodiment.

FIG. 13 is a diagram for explaining Kana-Kanji basic dictionary data of the second embodiment.

FIG. 14 is a diagram for explaining the Kana-Kana Katakana dictionary data of the second embodiment.

FIG. 15 is a diagram for explaining attached word dictionary data of the second embodiment.

FIG. 16 is a diagram for explaining a word candidate table according to the second embodiment.

FIG. 17 is a diagram for explaining a phrase candidate table according to the second embodiment.

FIG. 18 is a diagram for explaining the co-occurrence word dictionary data according to the second embodiment.

FIG. 19 is a diagram for explaining a Kanji output buffer of the second embodiment.

FIG. 20 is a diagram for explaining the homophony table of the second embodiment.

FIG. 21 is a diagram for explaining the first example dictionary data of the second embodiment.

FIG. 22 is a diagram for explaining the second example dictionary data of the second embodiment.

FIG. 23 is a diagram for explaining an example table of the second embodiment.

FIG. 24 is a diagram for explaining a four-character idiom table according to the second embodiment.

FIG. 25 is a diagram for explaining the four-character idiom dictionary data of the second embodiment.

FIG. 26 is a diagram for explaining the homophone output buffer of the second embodiment.

FIG. 27 is a diagram for explaining an example output buffer of the second embodiment.

FIG. 28 is a diagram for explaining the four-character idiom output buffer of the second embodiment.

FIG. 29 is a diagram for explaining inflection word notation data according to the second embodiment.

FIG. 30 is a diagram for explaining an example priority table of the second embodiment.

FIG. 31 is a diagram for explaining an example adjunct word table of the second embodiment.

FIG. 32 is a diagram showing display contents in an example display area of the second embodiment.

FIG. 33 is a diagram showing a four-character idiom display according to the second embodiment.

FIG. 34 is a diagram showing a homophone table according to the second embodiment.

FIG. 35 is a diagram showing an example display state of the next word in the second example.

[Explanation of symbols]

(1) keyboard (input unit), (1a) kana-kanji conversion key, (1b) example dictionary key (example display instruction means), (204) co-occurrence word dictionary, (205) first example dictionary data (storage means), (4) Control unit, (5) Output unit (display means), (5a) Example display area, (6) Kana-Kanji control unit (Kana-Kanji conversion unit) (9) Output candidate creation unit, (10) Example reference control unit (12) Example search processing section (example display availability determination means, example display order determination means), (16) Example output processing section (example generation means).

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Takayuki Furuwada, 2-18 Keihan Hondori, Moriguchi City, Osaka Prefecture Sanyo Electric Co., Ltd. (72) Masanori Ito 2-18, Keihan Hondori, Moriguchi City, Osaka Sanyo Electric Co., Ltd.

Claims (5)

[Claims] 1. When converting an input kana character string into a kanji-kana mixed character string, selecting a homonym using the co-occurrence word dictionary information and instructing a word for which an example is displayed. In the document creation device that creates example sentences using this co-occurrence word dictionary information, an example generation means (16) for generating example sentences from the co-occurrence word dictionary information, and an example for instructing word example display The display instruction means (1b) and the co-occurrence word dictionary information are searched based on this word, and the display propriety is judged using the example display propriety data associated with this co-occurrence word dictionary information. If it is determined that the example generation means (16) based on the instructed word
When it is determined that the example sentence is to be generated in No., it is provided with an example display availability determination means (12) that does not generate the example sentence and a display means (5) for displaying the generated example sentence. A document processing device characterized by: 2. When converting an input kana character string into a kanji-kana mixed character string, selecting a homonym using the co-occurrence word dictionary information and instructing a word for which an example is displayed. In the document creation device that creates example sentences using this co-occurrence word dictionary information, an example generation means (16) for generating example sentences from the co-occurrence word dictionary information, and an example for instructing word example display The display instruction means (1b) and the co-occurrence word dictionary information are searched based on this word, and the display order is determined using the example display order control data associated with this co-occurrence word dictionary information. Example display order determination means (12) for determining the display order of the example sentences generated by the example generation means (16), and the generated example sentences are displayed in the display order determined by the example display order determination means (12). A document comprising display means (5) Processing equipment. 3. A co-occurrence word dictionary (204) is used to select a homonym when converting an input kana character string into a kanji-kana mixed character string, and the co-occurrence word dictionary (20) is selected.
In the document creation device that creates a plurality of example sentences by 4) and displays them on the display means (5), in association with the co-occurrence word dictionary (204), a storage for storing control data for displaying the example sentences. A document processing apparatus comprising means (205). 4. The control data is data for determining whether to display the example sentence.
Document processor. 5. The document processing apparatus according to claim 3, wherein the control data is data for determining a priority order of display order of the example sentences.