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{ |
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"paper_id": "C82-1044", |
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"header": { |
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"generated_with": "S2ORC 1.0.0", |
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"date_generated": "2023-01-19T13:13:18.616010Z" |
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}, |
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"title": "AN ENGLISH-JAPANESE MACHINE TRANSLATION SYSTEM BASED ON FORMAL SEMANTICS OF NATURAL LANGUAGE", |
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"authors": [ |
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{ |
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"first": "Toyo-Aki", |
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"middle": [], |
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"last": "Nishida", |
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"suffix": "", |
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"affiliation": { |
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"laboratory": "", |
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"institution": "Kyoto University", |
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"location": { |
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"addrLine": "8akyo-ku", |
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"postCode": "606", |
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"settlement": "Kyoto", |
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"country": "JAPAN" |
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} |
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}, |
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"email": "" |
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}, |
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{ |
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"first": "Shuji", |
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"middle": [], |
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"last": "Doshita", |
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"suffix": "", |
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"affiliation": { |
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"laboratory": "", |
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"institution": "Kyoto University", |
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"location": { |
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"addrLine": "8akyo-ku", |
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"postCode": "606", |
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"settlement": "Kyoto", |
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"country": "JAPAN" |
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} |
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}, |
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"email": "" |
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} |
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], |
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"year": "", |
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"venue": null, |
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"identifiers": {}, |
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"abstract": "Tbls paper proposes a new model of machine translation. In this model, the lambda formula obtained from the syntactic and Semantic analysis of a source language sentence is viewed as a target language generating function and the target language sentence is obtained as a result of evaluating the formula by functional application or ~-calculus. This model provides a systematic and powerful way of incorporating human knowledge on the languages. A prototype is constructed on the LISP system. The performance was tested for four sample texts taken from existing technical reports and computer manuals.", |
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"paper_id": "C82-1044", |
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"abstract": [ |
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{ |
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"text": "Tbls paper proposes a new model of machine translation. In this model, the lambda formula obtained from the syntactic and Semantic analysis of a source language sentence is viewed as a target language generating function and the target language sentence is obtained as a result of evaluating the formula by functional application or ~-calculus. This model provides a systematic and powerful way of incorporating human knowledge on the languages. A prototype is constructed on the LISP system. The performance was tested for four sample texts taken from existing technical reports and computer manuals.", |
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"section": "Abstract", |
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"sec_num": null |
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"body_text": [ |
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{ |
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"text": "This paper proposes a functional model of machine translation and describes its applcation to English-Japanese machine translation. In this model, we aimed to achieve:", |
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"section": "INTRODUCTION", |
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"sec_num": null |
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}, |
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{ |
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"text": "-systematization of translation process, -lexicon based autonomous framework, and -a translation model based on semantic interpretation.", |
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"cite_spans": [], |
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"ref_spans": [], |
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"eq_spans": [], |
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"section": "INTRODUCTION", |
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"sec_num": null |
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}, |
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{ |
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"text": "Intermediate representation of this model is EFR (English-oriented Formal Repre~entatlon) and CPS (Conceptual Phrase Structure).", |
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"cite_spans": [], |
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"section": "INTERMEDIATE REPRESENTATION", |
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"sec_num": null |
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"text": "EFR is a logical language based on Cresswell's lambda eategorial language (Cresswell (1973) ), which can be considered to be a notationally simplified version of Montague Grammar (Montague (1974) , Dowry (1981) ). From an engineering point of view, EFR can be regarded as an artiflcial language in which each expression is unambiguous. So, there may be the cases in which more than one EFR expression can be associated with a given sentence. In such cases, ambiguities are resolved using inference, knowledge, or by human assistance.", |
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"cite_spans": [ |
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{ |
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"start": 74, |
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"end": 91, |
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"text": "(Cresswell (1973)", |
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"ref_id": "BIBREF0" |
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}, |
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{ |
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"start": 179, |
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"end": 195, |
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"text": "(Montague (1974)", |
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"ref_id": "BIBREF4" |
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}, |
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{ |
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"start": 198, |
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"end": 210, |
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"text": "Dowry (1981)", |
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"ref_id": "BIBREF3" |
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"section": "INTERMEDIATE REPRESENTATION", |
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"sec_num": null |
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"text": "CPS is an extended phrase structure in that (I) CPS is a more general element including syntactic knowledge on the concept, so (2) CPS is implemented as a framo and (3) CPS is not only a data structure which is an object under operation but also a function which can operate on other CPS's.", |
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"section": "INTERMEDIATE REPRESENTATION", |
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"sec_num": null |
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"text": "A CPS formula is a functional notation (lambda formula) of the operation sequence on CPS's. A CPS formula is evaluated to be a CPS or a functional value.", |
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"cite_spans": [], |
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"section": "INTERMEDIATE REPRESENTATION", |
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"sec_num": null |
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"text": "The evaluation process is defined by a (pure) LISP like interpreter.", |
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"section": "INTERMEDIATE REPRESENTATION", |
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"sec_num": null |
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"text": "Engllsh sentence analysis is done using~wo layered rules, pattern directed augmented context free rules (AUGCF rules) and production type procedural rules. AUGCF rule is a descriptive rule. Context free rule is extended in several points, (1) attached function for checking syntactic details and semantic acceptability, (2) Although lots of syntactic phenomena can be easily formelized with AUGCF rules, the computer cannot efficiently analyze input sentences only with them. One reason is that the computer nmst examine which rules are applicable in a given situation and determine which one is plausible. Such processings make the computer very much slow and inefficient.", |
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"cite_spans": [ |
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{ |
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"start": 320, |
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"end": 323, |
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"text": "(2)", |
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"ref_id": "BIBREF1" |
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} |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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}, |
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"text": "Another reason is that some kind of heuristic knowledge, which is sometimes referred to as knowledge on control (Davis (1980)), cannot be effectively incorporated into the AUGCF rules.", |
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"cite_spans": [], |
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"ref_spans": [], |
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"eq_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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"text": "The knowledge on control provides heuristics on when and how to use each rule. Condition -> actio~ formalism (production rule formalism) is considered to be suitable to write such level of knowledge.", |
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"cite_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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}, |
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{ |
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"text": "Our second level rule is obtained by attaching control informetion to each AUGCF rule and transforming the rule format. The type of procedural rules are: E-rule, U-rule, B-rule, and L-rule.", |
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"cite_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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}, |
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{ |
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"text": "-E-rule (expansion rule) is invoked when a goal is expected. E-rule specifies subgoal decomposition of the given goal. -U-rule (up-ped rule) is invoked when a parse tree node is generated. This rule further specifies additional goals and if all of them succeed, a new node will be constructed. This rule is used mainly for left recurslve type AUGCF rules.", |
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"cite_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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}, |
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{ |
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"text": "-B-rule (Bottom-up rule) is referred to by a bottom-up parser incorporated in the rule interpreter. -L-rule (Lexicon rule) is embedded in a dictionary and invoked when a key word is encountered in the given text.", |
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"cite_spans": [], |
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"ref_spans": [], |
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"eq_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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}, |
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{ |
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"text": "The rules RI and R2 are rewritten into procedural type rules as follows: Where RI', for example, says that: given a goal S then expand it into subgoals NP and VP; if both of them succeed then reduce them into an S node; at that time, a function subjvp checks subject-verb agreement; +10 is the score for S; *seml(*sem 2) is a p~ttern of the EFR expression for the S node, where *sem 1 denotes the EFR expression for its first son (NP), etc. If some anomaly is detected by those functional attachments, the application of the rule is rejected (functional augmentation of CF rule).", |
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"cite_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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}, |
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{ |
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"text": "goal=S \"~{T -*", |
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"cite_spans": [], |
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"ref_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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}, |
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"text": "A notion of a frame is employed in order to implement feature semantics. A frame is an extended property list in which syntactic and semantic features are described.", |
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"cite_spans": [], |
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"ref_spans": [], |
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"eq_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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"text": "By passing and checking consistency among such features, (mainly semantic) constraints are implemented.", |
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"cite_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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"text": "In practice, the knowledge incorporated in a system can never be total and complete, so human being ~hould help computer analyze input sentences. The human halp is limited to resolving ambiguities.", |
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"cite_spans": [], |
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"ref_spans": [], |
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"eq_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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"text": "In order to make the human diagnosis efficient, some diagnostic facilities are implemented.", |
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"cite_spans": [], |
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"ref_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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"text": "It is also important to construct and manage dictionaries. Dictionary manager is implemented to make human modification of dictionary flexible by use of pattern directed dictionary editing commands.", |
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"cite_spans": [], |
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"ref_spans": [], |
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"eq_spans": [], |
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"section": "SOURCE LANGUAGE ANALYSIS", |
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"sec_num": null |
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"text": "The interpretation of an EFR expression can be defined in the conceptual level. For example, given an EFR expression:", |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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{ |
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"text": "a(%y[a*(communication))(~x[(((*ap(for)(x))(facility))(y)])]),", |
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"cite_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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{ |
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"text": "which corresponds to a noun phrase \"a facility for communication\".", |
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"cite_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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"text": "A detailed description of the conceptual interpretation in our conceptual model (Nishida (1980) ) is given below. which becomes \"for the sake of (a) communication\" from (2). (4) the adjective concept obtained in (3) is applied as a function to the interpretation of \"facility\" (i.e., a noun concept \"facility\"). Thus we obtain a complex noun concept \"system for the sake of (a) facility\" for ((*ap(for))(x))(facility). (5) the application of a noun concept p to an individual concept q yields a sentence concept: \"q is a p.\" This interpretation rule is used for the fragment: (((*ap(for))(x))(facility))(y). The result is a sentence concept: \"something (y) is a facility for the sake of (a) communication.\" (6) Finally the interpretation of a given EFR expression results in a noun phrase concept: \"something y: such that y is a facility for the sake of (a) communication.\" This noun phrase concept is a higher order concept which gives a name to an individual: \"a facility for the sake of (a) co~m~unication.\" This higher order concept will be reduced if it is applied to a one place predicate (roughly speaking, a property like \"being constructed\", \"being an x such that the paper is concerned with", |
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{ |
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"start": 80, |
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"end": 95, |
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"text": "(Nishida (1980)", |
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"ref_id": "BIBREF5" |
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} |
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], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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{ |
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"text": "x\", etc.).", |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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"text": "The above process of interpretation is stepwise and includes no \"gap\" nor \"skip\". Such property is crucially important i n constructing large and complex systems including machine translation systems. This process can be simulated in the \"linguistic\" domain; our idea of target language generation is this:", |
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"cite_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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{ |
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"text": "each conceptual element is accompanied with a target language phrase structure which gives the name of the concept. -each semantic interpretation of a complex structure is accompanied with a syntactic operation of creating new phrase structure from those for function part and argument part conceptual elements. Thus, a functional application corresponds to a primitive syntactic operation of Japanese language.", |
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"cite_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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{ |
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"text": "CPS is defined to be a structure which conveys not only conceptual information on a concept but also syntactic infbrmation about the concept. All those information is structured as a frame.", |
|
"cite_spans": [], |
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"ref_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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{ |
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"text": "The descendant slot of a CPS is either a terminal value (lexicon frame) or a list of CPS's.", |
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"cite_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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"text": "Thus CPS can be linked as a tree structure.", |
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"cite_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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"text": "A CPS corresponding to a noun phrase: \"the typewriter\" looks like:", |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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"text": "[NP [DET 'the' with Q=DEFINITE] r 'typewriter' with CLASS=PHYSOBJ ] with NBR=SGL ]. LNOUN ......", |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"text": "A CPS works both as a data and as a function; it is sometimes applied to other CPS's to result in another CPS or functional value, or it sometimes is a data structure under some operation. Thus CPS is a higher order object. The semantics can be modeled in the notion of a categorial grammar.", |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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"text": "A CPS of an adjective concept, for example, meps a CPS of a noun concept into another (compound) CPS of a modified noun.", |
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"cite_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"text": "This principle can he written as: ADJ=NOUN/NOUN.", |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"text": "On the other hand, the adjective CPS can be modified by an adverbial CPS.", |
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"text": "Thus ADV=ADJ/ADJ. In practice, our system involves one step called the REFORM step after the CPS evaluation process. This step is needed mainly because, (I) some direct output is not readable; the content can be understood without ambiguity, but i\u00a3 is much redundant or not commonly used, or much mere worse (2) the output is semantically wrong. Such cases arises where the EFR expression extracted from the source language is not well defined to the language expression in question. This case occurs when the system designer commits misconception or fails to correctly capture the phenomenon. In principle, the second case is obviously bad but no theory has ever succeeded in medelling all phenomena in natural language.", |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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{ |
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"text": "So in practice, the second case is unavoidable.", |
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"cite_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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}, |
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"text": "The REFORM process uses heuristic rules to 'reform' those CPS structure into reasonable one.", |
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"cite_spans": [], |
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"ref_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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}, |
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"text": "Pattern directed transformation rules are used. Those rules are applied until no rule is applicable to the given CPS structure.", |
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"cite_spans": [], |
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"section": "INTERPRETATION OF EFR AND TARGET LANGUAGE GENERATION", |
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"sec_num": null |
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{ |
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"text": "A prototype of the system has been constructed on a personal LISP system (Voshita (1978)), which is developed on a minicomputer with LISP-oriented storage subsystem. As to the analysis module, sixth version is in use; as to the generation module, first version is in use. About two years since the last COLING conference at Tokyo were mainly devoted to the development.", |
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"section": "EXPERIMENTS", |
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"sec_num": null |
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}, |
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{ |
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"text": "At the first stage of experiment, sample sentences were tested for several sentence patterns. At the second stage, our purpose was to extend the system for practical test; to translate existing texts even if introducing human assists to some (reasonable) extent. Four sample texts (totally 40 sentences) selected from existing technical reports and computer menuals. Each of the s ~le texts orresponds to one section or a short chapter in the material. All s ences of each sample texts have been successfully translated into Japanese. No pre-editing is done except for three minor modifications to the original text (e.g., \"16-or 32-bit\" => \"16-bit or 32-bit\"). Human assist is limited to resolving ambiguities in the analysis phase. One example is shown in Fig.2 .", |
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"start": 758, |
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"end": 763, |
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"text": "Fig.2", |
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"ref_id": null |
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} |
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], |
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"section": "EXPERIMENTS", |
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"sec_num": null |
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}, |
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{ |
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"text": "This paper proposes a new approach to machine translation based on a functional semantics of natural langauge. The effectiveness of this approach is tested by experi~nts for short chapters and an abstract taken from existing technical reports and computer menuals.", |
|
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"section": "CONCLUSION", |
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"sec_num": null |
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} |
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], |
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"back_matter": [ |
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{ |
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"text": "This research was partially supported by Grant-in-Aid for Scientific Research. The authors want to thank Mr. Kiyoshi Agusa and Mr. Shigeo Sugimoto for providing conveniences of editing and printing this material.", |
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"section": "ACKNOWLEGDEMENT", |
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"sec_num": null |
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} |
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], |
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"bib_entries": { |
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"BIBREF0": { |
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"ref_id": "b0", |
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"title": "Logics and Languages", |
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"authors": [ |
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{ |
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"first": "M", |
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"middle": [ |
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"J" |
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], |
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"suffix": "" |
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"volume": "", |
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"FIGREF0": { |
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"text": "(I) conceptual interpretation of a(~y[ ... ]) associates a conceptual element \"something\" (individual concept) with the variable y. (2) conceptual interpretation of a*(communication)(~x[ ... ]) associates a conceptual element \"(a) communication\" with the variable x. (3) (*ap(for))(x) is interpreted as an adjective concept \"for the sake of x\",", |
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"FIGREF1": { |
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"type_str": "figure", |
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"text": "transforming one phrase by use of the information from another phrase.a (Ay [ (a* (communicatlon)) (a) eonTnuni~on/ / [ NOUN[ NOUN-MODF\" (aS ~5) ~ ~0 ~D] [ NOUN ~ ]] / f,,~ty .,'o. c,,) .o.,r~o,, j/ [S[NPaS~Gcr~:)][Np (aS ~) ~6Dtc~\u00a9-~][PRED\"O~ ]] something is a faci~ con~nication [Np(~ ~) (~S) ~D/C~O~D~ ] (some) facility for (a) communication Fig.l. Outline of a sample generation from an EFR expression.", |
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"FIGREF2": { |
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"type_str": "figure", |
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"text": "an outline of target language generation process for a phrase \"a facility for communication\". (CPS formula is onmited there.)", |
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} |
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} |
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} |
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} |