[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

JPS6344276A - Automatic generator for generated syntax - Google Patents

Automatic generator for generated syntax

Info

Publication number
JPS6344276A
JPS6344276A JP61187154A JP18715486A JPS6344276A JP S6344276 A JPS6344276 A JP S6344276A JP 61187154 A JP61187154 A JP 61187154A JP 18715486 A JP18715486 A JP 18715486A JP S6344276 A JPS6344276 A JP S6344276A
Authority
JP
Japan
Prior art keywords
sentence
natural language
grammar
language sentence
syntax
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
JP61187154A
Other languages
Japanese (ja)
Other versions
JPH0656614B2 (en
Inventor
Fumito Nishino
文人 西野
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Fujitsu Ltd
Original Assignee
Fujitsu Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fujitsu Ltd filed Critical Fujitsu Ltd
Priority to JP61187154A priority Critical patent/JPH0656614B2/en
Publication of JPS6344276A publication Critical patent/JPS6344276A/en
Publication of JPH0656614B2 publication Critical patent/JPH0656614B2/en
Anticipated expiration legal-status Critical
Expired - Fee Related legal-status Critical Current

Links

Landscapes

  • Machine Translation (AREA)

Abstract

PURPOSE:To prevent the level of syntax from dropping and to cope with complicated syntax by correctly generating generated syntax by a machine. CONSTITUTION:A natural language sentence analyzer 2 and a natural language sentence generator 3 translate an original text inputted to a reader 1 for a parallel translation sentence as a parallel translation sentence. A natural language sentence comparator 4 compares the translation with a translation given to the reader 1. If they disagree with each other, the comparator 4 decides that there are errors in the generated syntax or its shortage. A generated syntax error recognizer 5 recognizes the syntax deriving the errors, and a generated syntax correcting device 6 corrects the generated syntax. A generated syntax inspecting device 7 inspects whether the corrected generated syntax correctly functions with respect to translations on a right answer file 9, thereby automatically generating the generated syntax.

Description

【発明の詳細な説明】 〔概要〕 自然言語処理分野において、機械用の生成文法の開発を
しなければならないという問題を解決するため、生成文
法の誤りを自動的に認定し自動的に文法を修正すること
により、人間が機械用の生成文法を開発しないでもすむ
ようにしたものである。
[Detailed Description of the Invention] [Summary] In order to solve the problem of having to develop a generative grammar for machines in the field of natural language processing, we have developed a method that automatically identifies errors in generative grammars and automatically improves the grammar. By modifying it, humans no longer need to develop a generative grammar for machines.

〔産業上の利用分野〕[Industrial application field]

本発明は、自然言語処理における自然言語文生成のため
の生成文法の生成装置に関するものである。
The present invention relates to a generative grammar generating device for generating natural language sentences in natural language processing.

自然言語処理における自然言語文生成は、機械翻訳にお
ける対訳語文生成やデータベース上の知識を出力する場
合などに用いられ、正確な文生成を要求されるが、それ
に伴い文生成を行うために使用される生成文法は巨大化
・複雑化の傾向にある。このため、このような生成文法
を高精度に且つ容易に作成できる開発方法が必要とされ
る。
Natural language sentence generation in natural language processing is used to generate bilingual sentences in machine translation or to output knowledge from a database, and requires accurate sentence generation. Generative grammars tend to become larger and more complex. Therefore, there is a need for a development method that can easily create such generative grammars with high accuracy.

〔従来技術と問題点〕[Prior art and problems]

第4図は翻訳方式の概要を示す図である。第4図に示す
ように、日本語文の解析を行い、概念構造を作成する。
FIG. 4 is a diagram showing an outline of the translation method. As shown in Figure 4, a Japanese sentence is analyzed and a conceptual structure is created.

概念構造はトリー又はネットワーク構造をしている。概
念構造から目標言語(この場合は英語)を生成する過程
では、概念を表現する概念記号をもとに目標言語の単語
辞書から単語を抽出し、概念構造で示される入口地点の
アークが入るノードから処理を始め、そのノードは周り
のアークやその先のノードと、選択した単語の文法属性
を見ながら構文を決定し、形態素処理をする。これらの
規則を生成文法と呼んでいる。
The conceptual structure has a tree or network structure. In the process of generating a target language (English in this case) from a conceptual structure, words are extracted from the word dictionary of the target language based on the conceptual symbol expressing the concept, and the node where the arc of the entry point indicated in the conceptual structure enters is extracted. Processing starts from , and that node determines the syntax while looking at the surrounding arcs and nodes ahead of it, as well as the grammatical attributes of the selected word, and performs morphological processing. These rules are called generative grammars.

第5図は翻訳の例を示す図である。日英機械翻訳装置に
“彼は彼女に本を与えた”と言う日本語文を人力した場
合を想定する。“彼は彼女に本を与えた”と言う日本語
文が入力されると、翻訳装置は人力日本語文の意味を表
す概念構造を生成する。この概念構造において、「与え
る」から「彼女」に向うアークには相手と言う属性が付
加され、「与える」から「彼」に向うアークには行為者
と言う属性が付加され、「与える」から「本」に向うア
ークには対象物と言う属性が付加されている。
FIG. 5 is a diagram showing an example of translation. Suppose that a Japanese sentence such as ``He gave her a book'' is manually input into a Japanese-English machine translation device. When a Japanese sentence such as ``He gave her a book'' is input, the translation device generates a conceptual structure representing the meaning of the human-powered Japanese sentence. In this conceptual structure, the attribute "partner" is added to the arc from "give" to "her," the attribute "doer" is added to the arc from "give" to "him," and the attribute "doer" is added to the arc from "give" to "he." The arc heading toward the "book" has an attribute called an object attached to it.

「与える」から処理を行うとすると、「与える」を表す
英語が単語辞書から取り出される。「与える」に対応す
る英語“give”は、Dlと言う構文とT1と言う構
文を持っている。Dlと言う構文は、最初に行為者を示
す単語(この場合はhe)が来て、次に自分自身(この
場合はgive)が来て、次に相手を表す単語(この場
合はsheの目的格)が来て、最後に対象物を表す単語
(この場合はbook)が来ると言うものである。
If processing is performed from ``give'', the English word for ``give'' is retrieved from the word dictionary. The English word "give", which corresponds to "give", has a construction called Dl and a construction called T1. In the syntax Dl, the word that indicates the actor (in this case, he) comes first, then the person himself (in this case, give), and then the word that indicates the other party (in this case, the purpose of she). case), and finally the word representing the object (in this case, book).

T1と言う構文は、最初に行為者を表す単語が来て、次
に自分自身が来て、次に対象物を表す単語が来て、次に
toが来て、最後に相手を表す単語が来ると言うもので
ある。
In the construction T1, the word representing the actor comes first, then the word itself, then the word representing the object, then to, and finally the word representing the other party. It says it will come.

第6図は従来の生成文法の開発方法を説明する図である
。第6図に示すように、生成文法はエディタを通して人
間によって修正されていく。
FIG. 6 is a diagram illustrating a conventional method for developing a generative grammar. As shown in FIG. 6, the generative grammar is modified by humans through an editor.

〔解決しようとする問題点〕[Problem to be solved]

従来の生成−文法開発方法では、出力された文を人間が
見て誤っているかどうかを判断し、誤っている文法を探
し、修正するため、誤っている文法を探し出すのに手間
がかかり、修正した結果の文法がその文章にはうまく適
合しても以前に正しく生成されていた文章が正しく生成
できるかわからないといった問題を生じていた。
In the conventional generation-grammar development method, humans look at the output sentences to determine whether they are incorrect, search for incorrect grammar, and correct it, which takes time and effort to find incorrect grammar, and requires correction. Even if the resulting grammar fits the sentence well, it is unclear whether it will be able to correctly generate sentences that were previously generated correctly.

本発明は、この点に鑑みて創作されたものであって、生
成文法を機械によって正しく生成できるようになった生
成文法自動生成装置を提供することを目的としている。
The present invention was created in view of this point, and an object of the present invention is to provide an automatic generative grammar generation device that can correctly generate generative grammars by machine.

C問題点を解決するための手段〕 第1図は本発明の生成文法自動生成装置の原理図である
。第1図おいて、1は対訳文章読込装置、2は自然言語
文解析装置、3は自然言語文生成装置、4は自然言語文
比較装置、5は生成文法誤り認定装置、6は生成文法修
正装置、7は生成文法検査装置、8は生成文法、9は正
解ファイルである。
Means for Solving Problem C] FIG. 1 is a diagram showing the principle of an automatic generative grammar generation device of the present invention. In Figure 1, 1 is a bilingual text reading device, 2 is a natural language sentence analysis device, 3 is a natural language sentence generation device, 4 is a natural language sentence comparison device, 5 is a generative grammar error recognition device, and 6 is a generative grammar correction device. 7 is a generative grammar checking device, 8 is a generative grammar, and 9 is a correct answer file.

本発明では、対訳文章として対訳文章読込装置lに入力
された原文が、自然言語文解析装置2、自然言語文生成
装置3によって翻訳される。そして、その訳文と、対訳
文読込装置1に与えられた訳文とが自然言語文比較装置
4によって比較され、結果が異なる場合には生成文法の
誤りか、不足があると判定し、この誤りを導き出した文
法を生成文法誤り認定装置5で認定し、生成文法修正装
置6が生成文法を修正する。そして、生成文法検査装置
7が、修正した生成文法が今までの正解ファイル9中の
文章に対して正しく機能するかを検査することで、自動
的に生成文法が作成される。なお、生成文法検査装置7
から自然言語文解析装置2に至る線は、データの流れを
示しており、生成文法検査装置7で検査された文は、必
要に応じて解析からの過程を再実行する。
In the present invention, an original text input as a bilingual text into a bilingual text reading device 1 is translated by a natural language sentence analysis device 2 and a natural language sentence generation device 3. Then, the translated sentence and the translated sentence given to the bilingual sentence reading device 1 are compared by the natural language sentence comparison device 4, and if the results are different, it is determined that there is an error or deficiency in the generative grammar, and this error is corrected. The derived grammar is certified by the generative grammar error recognition device 5, and the generative grammar correcting device 6 corrects the generative grammar. Then, the generative grammar checking device 7 checks whether the modified generative grammar functions correctly for the sentences in the correct answer file 9 so far, thereby automatically creating a generative grammar. Note that the generative grammar checker 7
The line from to the natural language sentence analysis device 2 shows the flow of data, and the sentences inspected by the generative grammar inspection device 7 are re-executed from the analysis as necessary.

〔実施例〕〔Example〕

第2図は本発明によるイヌイツト語生成文法の生成過程
を示す図、第3図はイヌイツト語辞書を示す図である。
FIG. 2 is a diagram showing the generation process of an Inuit language generation grammar according to the present invention, and FIG. 3 is a diagram showing an Inuit language dictionary.

第2図において、<agent >は行為者を示し、■
は動詞を示し、<object)は対象物を示している
。また、<st> は文の中心となる概念を示している
。更に、■、■、・・・は生成処理の順序を表している
In Figure 2, <agent> indicates the actor, and ■
indicates a verb, and <object) indicates an object. Furthermore, <st> indicates the central concept of the sentence. Furthermore, ■, ■, . . . represent the order of generation processing.

先ず、対訳文章読込装置1に、英語文r11ikeph
ysical education Jとイヌイツト語
文rIqaijarumaqattaqtur+8a 
Jを入力し、自然言語解析装置2によって英語の意味構
造を解析し、その意味構造とイヌイツト語辞書をもとに
、自然言語文生成装置3によって1ikeがrumaq
attaq、 lがnga、physical edu
cationが1qaijaに対応することを手掛りと
して、ngarumaqattaqiqaijaを生成
出力する。
First, the English sentence r11ikeph is loaded into the bilingual sentence reading device 1.
ysical education J and Inuit language rIqaijarumaqattaqtur+8a
J is input, the semantic structure of English is analyzed by the natural language analysis device 2, and based on the semantic structure and the Inuit dictionary, 1ike is rumaq by the natural language sentence generation device 3.
attaq, l is nga, physical edu
Using the fact that cation corresponds to 1qaija as a clue, ngarumaqattaqiqaija is generated and output.

この生成文と対訳文章読込装置1によって読み込まれた
イヌイツト語文とを自然言語文比較装置4により比較す
ることによって、この生成文が正解と異なることを認識
する。次に、文法誤り認1定装置5によって、自然言語
文生成装置3で使用された文法規則を調べることにより
、生成文法<agent > V <object>と
いう文法の適用が誤りであることを認定する。生成文法
修正装置6により、前記文法を<object>Vtu
<agent >という文法に修正すれば良いことを認
定し、生成文法8を修正する。この文法の修正後、原文
を再び自然言語文解析装置2に与え直すことで、再翻訳
して正しい翻訳が得られることを確認し、正解ファイル
9に当該対訳文を登録する。次にrl don’t h
ave a wife JとrNuliaqanngi
ttunga Jを与え、英語解析を行い、イヌイツト
語文を生成するとrNuliaqatungajとなっ
て、否定を表す単語nngitをtuの前に必要ならば
付は加えるように、文法を< object>V [<
not >コtu<agent >と修正する。その後
、この文章が正しく生成され、また前のrlqaija
rumaqattaqtunga Jに対しても正しく
生成されることを確認する。このようにして、対訳語を
与え、翻訳及び文法の修正を繰り返していくことによっ
て、イヌイツト語生成文法が作成されていく。
By comparing this generated sentence with the Inuit sentence read by the bilingual sentence reading device 1 using the natural language sentence comparison device 4, it is recognized that this generated sentence is different from the correct answer. Next, the grammar error recognition device 5 examines the grammar rules used by the natural language sentence generation device 3 to determine that the application of the generative grammar <agent>V <object> is incorrect. . The generative grammar correction device 6 converts the grammar into <object>Vtu
It is recognized that it is sufficient to modify the grammar to <agent>, and generative grammar 8 is modified. After correcting this grammar, the original sentence is given again to the natural language sentence analysis device 2 to confirm that a correct translation can be obtained through retranslation, and the bilingual sentence is registered in the correct answer file 9. Next rl don't h
ave a wife J and rNuliaqanngi
If you give ttunga J, perform English analysis, and generate an Inuit sentence, it becomes rNuliaqatungaj, and the grammar is changed to <object>V [<
Correct it as not>kotu<agent>. Then this sentence will be generated correctly and also the previous rlqaija
Confirm that it is generated correctly for rumaqattaqtunga J as well. In this way, an Inuit language generative grammar is created by providing bilingual words and repeating translation and grammar correction.

〔発明の効果〕〔Effect of the invention〕

以上の説明から明らかなように、本発明によれば、生成
文法を人間が生成することもなく、また今までに正しく
生成された文章の生成は保証されるため、文法のレベル
・ダウンを防ぎ、複雑な文法にも対処することができる
As is clear from the above explanation, according to the present invention, there is no need for humans to generate generative grammar, and the generation of sentences that have been correctly generated up to now is guaranteed, thus preventing the level of grammar from decreasing. , can also handle complex grammar.

【図面の簡単な説明】[Brief explanation of drawings]

第1図は本発明の詳細な説明する図、第2図はイヌイツ
ト語生成文法の生成例を示す図、第3図はイヌイツト語
の辞書の例を示す図、第4図は翻訳方式の概要を示す図
、第5図は翻訳の例を示す図、第6図は従来の生成文法
の開発の方法を示す図である。 1・・・対訳文章読込装置、2・・・自然言語文解析装
置、3・・・自然言語文生成装置、4・・・自然言語文
比較装置、5・・・生成文法誤り認定装置、6・・・生
成文法修正装置、7・・・生成文法検査装置、8・・・
生成文法、9・・・正解ファイル。
Figure 1 is a diagram explaining the present invention in detail, Figure 2 is a diagram showing a generation example of an Inuit language production grammar, Figure 3 is a diagram showing an example of an Inuit language dictionary, and Figure 4 is an overview of the translation method. FIG. 5 is a diagram showing an example of translation, and FIG. 6 is a diagram showing a conventional method for developing generative grammar. DESCRIPTION OF SYMBOLS 1... Bilingual text reading device, 2... Natural language sentence analysis device, 3... Natural language sentence generation device, 4... Natural language sentence comparison device, 5... Generative grammar error recognition device, 6 ...Generative grammar correction device, 7...Generative grammar check device, 8...
Generative grammar, 9... Correct answer file.

Claims (1)

【特許請求の範囲】 対訳文章読込装置(1)と、 この対訳文章読込装置(1)より読み込まれた文章の原
文章を解析する自然言語文解析装置(2)と、この自然
言語文解析装置(2)によって解析された結果から対訳
文を生成する自然言語文生成装置(3)と、 この自然言語文生成装置(3)によって得られた自然言
語文と前記対訳文章読込装置(1)によって読み込まれ
た対訳文章の訳文とを比較する自然言語文比較装置(4
)と、 この自然言語文比較装置(4)によって、自然言語文生
成装置(3)によって得られた文が対訳文章読込装置(
1)によって読み込まれた訳文と異なると判定されたと
き、自然言語文生成装置(3)によってどのような過程
で文章が生成されたかを調べる生成文法誤り認定装置(
5)と、 誤っている文法を修正、削除ないしは文法を自動的に追
加する生成文法修正装置(6)と、修正した結果の文法
が以前正しく生成されていた文章にも悪影響を与えず正
しく文が生成できるかどうかを検査する生成文法検査装
置(7)とを有することを特徴とする生成文法自動生成
装置。
[Claims] A bilingual text reading device (1), a natural language sentence analyzing device (2) that analyzes the original text of the text read by the bilingual text reading device (1), and this natural language sentence analyzing device A natural language sentence generation device (3) that generates a bilingual sentence from the results analyzed by (2), and a natural language sentence obtained by this natural language sentence generation device (3) and the bilingual sentence reading device (1). A natural language sentence comparison device (4) that compares the translated text of the read parallel text.
), and the natural language sentence comparison device (4) converts the sentence obtained by the natural language sentence generation device (3) into the bilingual sentence reading device (
When it is determined that the sentence is different from the translated text read by 1), the generative grammar error recognition device (3) examines the process by which the sentence was generated by the natural language sentence generation device (3).
5), a generative grammar correction device (6) that automatically corrects or deletes incorrect grammar or adds grammar, and a generative grammar correction device (6) that automatically corrects or deletes incorrect grammar, and that corrects the corrected grammar without adversely affecting sentences that were previously generated correctly. 1. A generative grammar automatic generation device comprising: a generative grammar checking device (7) for checking whether a generative grammar can be generated.
JP61187154A 1986-08-09 1986-08-09 Generation grammar automatic generation device Expired - Fee Related JPH0656614B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP61187154A JPH0656614B2 (en) 1986-08-09 1986-08-09 Generation grammar automatic generation device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP61187154A JPH0656614B2 (en) 1986-08-09 1986-08-09 Generation grammar automatic generation device

Publications (2)

Publication Number Publication Date
JPS6344276A true JPS6344276A (en) 1988-02-25
JPH0656614B2 JPH0656614B2 (en) 1994-07-27

Family

ID=16201066

Family Applications (1)

Application Number Title Priority Date Filing Date
JP61187154A Expired - Fee Related JPH0656614B2 (en) 1986-08-09 1986-08-09 Generation grammar automatic generation device

Country Status (1)

Country Link
JP (1) JPH0656614B2 (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5323310A (en) * 1991-02-14 1994-06-21 The British And Foreign Bible Society Analyzing textual documents
US5646840A (en) * 1992-11-09 1997-07-08 Ricoh Company, Ltd. Language conversion system and text creating system using such
CN1323811C (en) * 2003-04-29 2007-07-04 远藤工业株式会社 Spring balancer

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5323310A (en) * 1991-02-14 1994-06-21 The British And Foreign Bible Society Analyzing textual documents
US5646840A (en) * 1992-11-09 1997-07-08 Ricoh Company, Ltd. Language conversion system and text creating system using such
US5652896A (en) * 1992-11-09 1997-07-29 Ricoh Company, Ltd. Language conversion system and text creating system using such
US5675815A (en) * 1992-11-09 1997-10-07 Ricoh Company, Ltd. Language conversion system and text creating system using such
US5845143A (en) * 1992-11-09 1998-12-01 Ricoh Company, Ltd. Language conversion system and text creating system using such
CN1323811C (en) * 2003-04-29 2007-07-04 远藤工业株式会社 Spring balancer

Also Published As

Publication number Publication date
JPH0656614B2 (en) 1994-07-27

Similar Documents

Publication Publication Date Title
US6920419B2 (en) Apparatus and method for adding information to a machine translation dictionary
EP1351158A1 (en) Machine translation
US8209166B2 (en) Apparatus, method, and computer program product for machine translation
US20050137853A1 (en) Machine translation
US20050060160A1 (en) Hybrid automatic translation apparatus and method employing combination of rule-based method and translation pattern method, and computer-readable medium thereof
KR100530154B1 (en) Method and Apparatus for developing a transfer dictionary used in transfer-based machine translation system
Varshini et al. A recognizer and parser for basic sentences in telugu using cyk algorithm
JPH0261763A (en) Mechanical translation equipment
JPS6344276A (en) Automatic generator for generated syntax
JP2632806B2 (en) Language analyzer
Germann Making semantic interpretation parser-independent
JPH09325673A (en) Translation sentence correction supporting device
Kitamura et al. Practical machine translation system allowing complex patterns
Rosé et al. Recovering from parser failures: A hybrid statistical/symbolic approach
JP3339006B2 (en) Parallel Noun Phrase Processor in Machine Translation Equipment
JP4033089B2 (en) Natural language processing system, natural language processing method, and computer program
JP2000259631A (en) Machine translation proofreading device
JP2003006193A (en) Device and method for machine translation
JP4036172B2 (en) Natural language processing system, natural language processing method, and computer program
JP2504449B2 (en) Japanese phrase interdependency analysis device
JP2994539B2 (en) Machine translation equipment
JPH03127264A (en) Mechanical translation system for sentence including parentheses
JPH08278973A (en) Parallel phrase analyzing device and learning data generating device
JPH04282764A (en) Non-sentence translating device
KR19980036108A (en) Automatic Grammar Correction of Concept-based Multilingual Translation System

Legal Events

Date Code Title Description
LAPS Cancellation because of no payment of annual fees