| { |
| "paper_id": "P84-1034", |
| "header": { |
| "generated_with": "S2ORC 1.0.0", |
| "date_generated": "2023-01-19T08:21:04.964549Z" |
| }, |
| "title": "A PROPER TREATMEMT OF SYNTAX AND SEMANTICS IN MACHINE TRANSLATION", |
| "authors": [ |
| { |
| "first": "\u00a5oshihiko", |
| "middle": [], |
| "last": "Nitta", |
| "suffix": "", |
| "affiliation": { |
| "laboratory": "", |
| "institution": "Koichiro Ishihara Systems Development Laboratory", |
| "location": { |
| "addrLine": "Ltd. 1099 Ohzenji Asao-ku, Kawasaki-shi", |
| "postCode": "215", |
| "settlement": "Hitachi", |
| "country": "JAPAN" |
| } |
| }, |
| "email": "" |
| }, |
| { |
| "first": "Atsushi", |
| "middle": [], |
| "last": "Okajima", |
| "suffix": "", |
| "affiliation": { |
| "laboratory": "", |
| "institution": "Koichiro Ishihara Systems Development Laboratory", |
| "location": { |
| "addrLine": "Ltd. 1099 Ohzenji Asao-ku, Kawasaki-shi", |
| "postCode": "215", |
| "settlement": "Hitachi", |
| "country": "JAPAN" |
| } |
| }, |
| "email": "" |
| }, |
| { |
| "first": "Hiroyuki", |
| "middle": [], |
| "last": "Kaji", |
| "suffix": "", |
| "affiliation": { |
| "laboratory": "", |
| "institution": "Koichiro Ishihara Systems Development Laboratory", |
| "location": { |
| "addrLine": "Ltd. 1099 Ohzenji Asao-ku, Kawasaki-shi", |
| "postCode": "215", |
| "settlement": "Hitachi", |
| "country": "JAPAN" |
| } |
| }, |
| "email": "" |
| } |
| ], |
| "year": "", |
| "venue": null, |
| "identifiers": {}, |
| "abstract": "", |
| "pdf_parse": { |
| "paper_id": "P84-1034", |
| "_pdf_hash": "", |
| "abstract": [], |
| "body_text": [ |
| { |
| "text": "Japanese machine translation, the syntax directed approach is effective where the Heuristic Parsing Model (HPM) and the Syntactic Role System play important roles. For Japanese-English translation, the semantics directed approach is powerful where the Conceptual Dependency Diagram (CDD) and the Augmented Case Marker System (which is a kind of Semantic Role System) play essential roles.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "", |
| "sec_num": null |
| }, |
| { |
| "text": "Some examples of the difference between Japanese sentence structure and English sentence structure, which is vital to machine translation~ are also discussed together with various interesting ambiguities.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "", |
| "sec_num": null |
| }, |
| { |
| "text": "We have been studying machine translation between Japanese and English for several years. Experiences gained in systems development and in linguistic data investigation suggest that the essential point in constructing a practical machine translation system is in the appropriate blending of syntax directed processing and the semantics directed processing.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "In order to clarify the above-mentioned suggestion, let us compare the characteristics of the syntax directed approach with those of the semantics directed approach.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "The advantages of the syntax directed approach are as follows: (i) It is not so difficult to construct the necessary linguistic data for syntax directed processors because the majority of these data can be reconstructed from already established and well-structured lexical items such as verb pattern codes and parts of speech codes, which are overflowingly abundant in popular lexicons.", |
| "cite_spans": [ |
| { |
| "start": 63, |
| "end": 66, |
| "text": "(i)", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "(2) The total number of grammatical rules necessary for syntactic processing usually stays within a controllable range.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "(3) The essential aspects of syntactic processing are already well-known, apart from efficiency problems.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "The disadvantage of the syntax directed approach is its insufficient ability to resolve various ambiguities inherent in natural languages.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "On the other hand, the advantages of the semantics directed approach are as follows: (i) The meaning of sentences or texts can be grasped in a unified form without being affected by the syntactic variety.", |
| "cite_spans": [ |
| { |
| "start": 85, |
| "end": 88, |
| "text": "(i)", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "(2) Semantic representation can play a pivotal role for language transformation and can provide a basis for constructing a transparent machine translation system, because semantic representation is fairly independent of the differences in language classes.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "(3) Consequently, semantics directed internal representation can produce accurate translations.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "The disadvantages of the semantics directed approach are as follows:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "(I) It is not easy to construct a semantic lexicon which covers real world phenomena of a reasonably wide range.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "The It is not entirely possible to distinguish a syntax directed approach from a semantics directed approach, because syntax and semantics are always performing their linguistic functions reciprocally\u2022 As Wilks [16] points out, it is plausible but a great mistake to identify syntactic processing with superficial processing, or to identify semantic processing with deep processing. The term \"superficial\" or \"deep\" only reflects the intuitive distance from the language representation in (superficial) character strings or from the language representation in our (deep) minds. Needless to say, machine translation inevitably has something to do with superficial processing\u2022 ", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 4, |
| "end": 327, |
| "text": "It is not entirely possible to distinguish a syntax directed approach from a semantics directed approach, because syntax and semantics are always performing their linguistic functions reciprocally\u2022 As Wilks [16] points out, it is plausible but a great mistake to identify syntactic processing with superficial", |
| "ref_id": "TABREF9" |
| } |
| ], |
| "eq_spans": [], |
| "section": "I INTRODUCTION", |
| "sec_num": null |
| }, |
| { |
| "text": "Output Japanese Sentence representations.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "G.", |
| "sec_num": null |
| }, |
| { |
| "text": "An example of phrase strucure type representation, which we call HPM (Heuristic Parsing Model), is illustrated in Figure 2 .", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 114, |
| "end": 122, |
| "text": "Figure 2", |
| "ref_id": "FIGREF1" |
| } |
| ], |
| "eq_spans": [], |
| "section": "G.", |
| "sec_num": null |
| }, |
| { |
| "text": "In Figure 2 , a parsed tree is composed of two substructures.", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 3, |
| "end": 11, |
| "text": "Figure 2", |
| "ref_id": "FIGREF1" |
| } |
| ], |
| "eq_spans": [], |
| "section": "G.", |
| "sec_num": null |
| }, |
| { |
| "text": "One is \"tree ( ~/ ),\" representing a compulsory dependency relation, and the other is \"link (k~),\"", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "G.", |
| "sec_num": null |
| }, |
| { |
| "text": "representing an optional dependency relation. Each node corresponds to a certain constituent of the sentence.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "G.", |
| "sec_num": null |
| }, |
| { |
| "text": "The most important constituent is a \"phrasal element (PE)\" which is composed of one or more word element(s) and carries a part of the sentential meaning in the smallest possible form. PE's are mutually exclusive.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "G.", |
| "sec_num": null |
| }, |
| { |
| "text": "In Figure 2 , PE's are shown by using the \"segmenting marker ", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 3, |
| "end": 11, |
| "text": "Figure 2", |
| "ref_id": "FIGREF1" |
| } |
| ], |
| "eq_spans": [], |
| "section": "G.", |
| "sec_num": null |
| }, |
| { |
| "text": "Tare beginning (GOV)T, where the terminologies in parentheses are the syntactic roles which will be discussed later.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "A \"clausal element (CE)\" is composed of one or more PE('s) which carries a part of sentential meaning in a nexus-like form.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "A CE roughly corresponds to a Japanese simple sentence such as:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| { |
| "text": "\"%{wa/ga/wo/no/ni} ~ {suru/dearu} [koto] .\" CE's allow mutual intersection.", |
| "cite_spans": [ |
| { |
| "start": 34, |
| "end": 40, |
| "text": "[koto]", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "Typical examples are the underlined parts in the following: \"It is important for you to do so.\" \"... intended to yield a fifth generation system.\"", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "One interesting example in Figure 2 may be the part \"With some help from overseas\", which is treated as only two consecutive phrasal elements.", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 27, |
| "end": 35, |
| "text": "Figure 2", |
| "ref_id": "FIGREF1" |
| } |
| ], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "This is the typical result of a syntax directed parser.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "In the case of a semantics directed parser, the above-mentioned part will be treated as a clausal element. This is because the meaning of this part is \"(by) getting some help from overseas\" or the like, which is rather clausal than phrasal.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "(2) Syntax directed processors are effective and powerful to get phrase structure type parsed trees.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "Our A typical example of the semantic filter is illustrated in Figure 3 A bird could also use binoculars. One noteworthy point is that the thesaurus for controlling the semantic fields or semantic features of words should be constructed in an appropriate form (such as word hierarchy) so as to avoid the so-called combinatorial explosion of the number of selective restriction rules.", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 63, |
| "end": 71, |
| "text": "Figure 3", |
| "ref_id": null |
| } |
| ], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| { |
| "text": "(6) For the Japaneses sentence generating process, it may be necessary to devise a very complicated semantic processor if a system to produce natural idiomatic Japanese sentences is desired.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "But the majority of Japanese users may tolerate awkward word-by-word translation and understand its meaning.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "Thus we have concluded that our research efforts should give priority to the syntax directed analysis of English sentences.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| "text": "The semantics directed generation of Japanese sentences might not be an urgent issue; rather it should be treated as a kind of profound basic science to be studied without haste. For example, in Figure 2 , the verb \"yield\" has at least two different meanings (and consequently has at least two different Japanese equivalents):", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 195, |
| "end": 203, |
| "text": "Figure 2", |
| "ref_id": "FIGREF1" |
| } |
| ], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "\"yield\"-->I\"produce\" (ffi Umidasu)", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| { |
| "text": "[\"concede\" (ffi Yuzuru).", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| { |
| "text": "But it is neither easy nor certain how to devise a filter to distinguish the above two meanings mechanically.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| { |
| "text": "Thus we need some human aids such as post-editing and inter-editing. (9) As for the pertinent selection of function words such as postpositions, there are no formal computational rules to perform it.", |
| "cite_spans": [ |
| { |
| "start": 69, |
| "end": 72, |
| "text": "(9)", |
| "ref_id": "BIBREF8" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| { |
| "text": "So we must find and store heuristic rules empirically and then make proper use of them.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| { |
| "text": "Some heruistic rules to select appropriate Japanese postpositions are shown in Table 5 . (2) , the heuristic approach was also found to be effective in segmenting the input English sentence into a sequence of phrasal elements, and in structuring them into a tree-llke dependency diagram (cf. Figure 2 ). is identical to the above first formula. This convention may be different from the one defined by Hays [4] . Our convention was introduced to cope with the above-mentioned flexible word ordering in Japanese sentences.", |
| "cite_spans": [ |
| { |
| "start": 89, |
| "end": 92, |
| "text": "(2)", |
| "ref_id": "BIBREF1" |
| }, |
| { |
| "start": 407, |
| "end": 410, |
| "text": "[4]", |
| "ref_id": "BIBREF3" |
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| ], |
| "ref_spans": [ |
| { |
| "start": 79, |
| "end": 86, |
| "text": "Table 5", |
| "ref_id": "TABREF6" |
| }, |
| { |
| "start": 292, |
| "end": 300, |
| "text": "Figure 2", |
| "ref_id": "FIGREF1" |
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| ], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| "text": "(4) The aforementioned dependency relationships can be represented as a linking topology, where each link has one governor node and one dependant node as its top and bottom terminal point ( Figure 4 ). (5) The links are labeled with case markers. Our case marker system is obtained by augmenting the traditional case markers such as Fillmore's [3] from the standpoint of machine translation. For the PPN-NPN link, its label usually represents agent, object, goal, location, topic, etc.", |
| "cite_spans": [ |
| { |
| "start": 203, |
| "end": 206, |
| "text": "(5)", |
| "ref_id": "BIBREF4" |
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| "start": 345, |
| "end": 348, |
| "text": "[3]", |
| "ref_id": "BIBREF2" |
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| { |
| "start": 190, |
| "end": 199, |
| "text": "Figure 4", |
| "ref_id": null |
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| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
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| "text": "For the PPN-PPN link, its label is usually represent causality, temporality, restrictiveness, etc. (cf. Figure 4 ). (Table 6 ). 7The reason for the large number of optional case markers is that the detailed classification of optional cases is very useful for making an appropriate selection of prepositions and participles ( Table 7 ).", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 104, |
| "end": 112, |
| "text": "Figure 4", |
| "ref_id": null |
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| { |
| "start": 116, |
| "end": 124, |
| "text": "(Table 6", |
| "ref_id": "TABREF9" |
| }, |
| { |
| "start": 325, |
| "end": 332, |
| "text": "Table 7", |
| "ref_id": "TABREF10" |
| } |
| ], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
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| "text": "(g) Each NPN is to be labeled with some properly selected semantic features which are under the control of a thesaurus type lexicon. Semantic features are effective to disambiguate predicative dependency so as to produce an appropriate English verb phrase. (9) The essential difference between a Japanese sentence and the equivalent English sentence can be grasped as the difference in the mode of PPN selections, taken from the viewpoint of conceptual dependency diagram ( Figure 51 . Once an appropriate PPN selection is made, it will be rather simple and mechanical to determine the rest of the dependency topology. (I0) Thus the essential task of Japanese-English translation can be reduced to the task of constructing the rules for transforming the dependency topology by changing PPNs, while preserving the meaning of the original dependency topology (cf. Figure 5 ).", |
| "cite_spans": [ |
| { |
| "start": 257, |
| "end": 260, |
| "text": "(9)", |
| "ref_id": "BIBREF8" |
| } |
| ], |
| "ref_spans": [ |
| { |
| "start": 474, |
| "end": 483, |
| "text": "Figure 51", |
| "ref_id": "FIGREF0" |
| }, |
| { |
| "start": 862, |
| "end": 870, |
| "text": "Figure 5", |
| "ref_id": null |
| } |
| ], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
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| { |
| "text": "(Ill All the aforementioned findings have something to do with the semantic directed approach.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "Once the English oriented conceptual dependency diagram is obtained, the rest of the translation process is rather syntactic.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "That is, the phrase structure generation can easily be handled with somewhat traditional syntax directed processors.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "(12) As is well known, the Japanese language has a very high degree of complexity and ambiguity mainly caused by frequent ellipsis and functional multiplicity, which creates serious obstacles for the achievement of a totally automatic treatment of \"raw\" Japanese sentences.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "(ex i) \"Sakana wa Taberu.\" (fish) (eat) has at least two different interpretations:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "\u2022 \"[Sombody] can eat a fish.\" . \"The fish may eat [something] .\" ~\" ilnking through \"AND\" Conjunction BT Conjunction through \"BUT\" (Optional)", |
| "cite_spans": [ |
| { |
| "start": 50, |
| "end": 61, |
| "text": "[something]", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "......... (ex 2) \"Kawaii Ningyou wo Motteiru Onnanoko.\" (lovely) (doll) (carry) (girl) has also two different interpretations:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "\"The lovel~ ~irl who carries a doll with her.\" \"The girl who carries a lovel[ doll with her.\"", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "(13) Thus we have judged that some sub-Japanese language should be constructed so as to restrict the input Japanese sentences within a range of clear tractable structures. The essential restrictions given by the sub-language should be concerned with the usage of function words and sentential embeddings. Suru (=Make)-type CDD Figure 5 Difference between Japanese and English Grasped Through CDD (IA) A sub-language approach will not fetter the users, if a Japanese-Engllsh translation system is used as an English sentence composing aid for Japanese people.", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 327, |
| "end": 335, |
| "text": "Figure 5", |
| "ref_id": null |
| } |
| ], |
| "eq_spans": [], |
| "section": "T,(co~)T, Tthe Japanese (SUBJ)T and", |
| "sec_num": null |
| }, |
| { |
| "text": "We have found that there are some proper approaches to the treatment of syntax and semantics from the viewpoint of machine translation. Our conclusions are as follows: (i) In order to construct a practical English-Japanese machine translation system, it is advantageous to take the syntax directed approach, in which a syntactic role system plays a central role, together with phrase structure type internal representation (which we call HPM).", |
| "cite_spans": [ |
| { |
| "start": 168, |
| "end": 171, |
| "text": "(i)", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "V CONCLUSION", |
| "sec_num": null |
| }, |
| { |
| "text": "(2) In English-Japanese machine translation, syntax should be treated in a heuristic manner based on actual human translation methods. Semantics plays an assistant role in disambiguating the dependency among phrases.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "V CONCLUSION", |
| "sec_num": null |
| }, |
| { |
| "text": "(3) In English-Japanese machine translation, an output Japanese sentence can be obtained directly from the internal phrase structure representation (HPM) which is essentially a structured set of syntactic roles. Output sentences from the above are, of course, a kind of literal translation of stilted style, but no doubt they are understandable enough for practical use. 4In order to construct a practical Japanese-English machine translation system, it is advantageous to take the approach in which semantics plays a central role together with conceptual dependency type internal representation (which we call CDD).", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "V CONCLUSION", |
| "sec_num": null |
| }, |
| { |
| "text": "Japanese-English machine translation, augmented case markers play a powerful semantic ro le. (6) In Japanese-English machine translation, the essential part of language transformation between Japanese and English can be performed in terms of changing dependency diagrams (CDD) which involves predicate replacements.", |
| "cite_spans": [ |
| { |
| "start": 93, |
| "end": 96, |
| "text": "(6)", |
| "ref_id": "BIBREF5" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(5) In", |
| "sec_num": null |
| }, |
| { |
| "text": "One further problem concerns establishing a practical method of compensating a machine translation system for its mistakes or limitations caused by the intractable complexities inherent to natural languages. This problem may be solved through the concept of sublanguage, pre-editing and post-editing to modify source/target languages.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(5) In", |
| "sec_num": null |
| }, |
| { |
| "text": "The sub-Japanese language approach in particular seems to be effective for Japanese-English machine translaton. One of our current interests is in a proper treatment of syntax and semantics in the sublanguage approach.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(5) In", |
| "sec_num": null |
| } |
| ], |
| "back_matter": [], |
| "bib_entries": { |
| "BIBREF0": { |
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| "links": null |
| } |
| }, |
| "ref_entries": { |
| "FIGREF0": { |
| "num": null, |
| "type_str": "figure", |
| "uris": null, |
| "text": "Configuration of Machine Translation System: ATHENE [6] TWith .... helpTf ........... Tj~the Jap ..... Tare beglnningTa 10-year R&D effortTintendedTto yield~a fifth g ..... tion systemT.CP: Clausal Element \u2022 SE: Sentence \u2022 This sample English sentence is taken from Datamation Jan. 1982." |
| }, |
| "FIGREF1": { |
| "num": null, |
| "type_str": "figure", |
| "uris": null, |
| "text": "An Example of Phrase Structure Type Representation (I) The essential structure of English sentences should be grasped by phrase structure type" |
| }, |
| "FIGREF2": { |
| "num": null, |
| "type_str": "figure", |
| "uris": null, |
| "text": "(T)\", such as TWith some help (ADVL)[, [from overseas (ADJV)[j" |
| }, |
| "FIGREF3": { |
| "num": null, |
| "type_str": "figure", |
| "uris": null, |
| "text": ". The semantic filter may operate along with selective restriction rules such as: \u2022 N22 (Animal) + with + N753 (Accessory) Plausible [': N22 is equipped with N753] \u2022 V21 (Watching-Action) + with + N541 (Watching Instrument) ~ OK [vV21 by using N541 as an instrument] The semantic filter is not complete, especially for metaphorical expressions." |
| }, |
| "FIGREF4": { |
| "num": null, |
| "type_str": "figure", |
| "uris": null, |
| "text": "The virtual storage access method enables the efficient input-output processing to a large capacity data set." |
| }, |
| "TABREF0": { |
| "content": "<table><tr><td>II SYNTAX AND SEMANTICS</td><td/><td/><td/><td/><td/></tr><tr><td/><td/><td/><td/><td/><td/><td>main reason for this</td></tr><tr><td colspan=\"3\">difficulty</td><td>is</td><td colspan=\"2\">that</td><td>a</td><td>well-established</td><td>and</td></tr><tr><td colspan=\"7\">widely-accepted method of describing semantics</td></tr><tr><td>does</td><td colspan=\"2\">not</td><td colspan=\"2\">exist.</td><td/><td>(For</td><td>strongly</td><td>restricted</td></tr><tr><td colspan=\"6\">statements or topics,</td><td>of course, there exist</td></tr><tr><td colspan=\"7\">well-elaborated methods such as Montague grammar</td></tr><tr><td colspan=\"7\">[2], Script and MOP (Memory Organization Packet)</td></tr><tr><td colspan=\"3\">theory [13],</td><td colspan=\"4\">Procedural</td><td>Semantics [14],</td><td>and</td></tr><tr><td colspan=\"7\">Semantic Interlingual Representation [15].)</td></tr><tr><td colspan=\"7\">(2) even if you could devise a fairly acceptable</td></tr><tr><td colspan=\"7\">method to describe semantics, the total number of</td></tr><tr><td colspan=\"7\">semantic rule descriptions may expand beyond all</td></tr><tr><td colspan=\"4\">manageable limits.</td><td/><td/></tr><tr><td colspan=\"7\">Therefore, we think that it is necessary to</td></tr><tr><td colspan=\"7\">seek proper combinations of syntactic processing</td></tr><tr><td colspan=\"7\">and semantic processing so as to compensate for</td></tr><tr><td colspan=\"7\">the disadvantages of each.</td></tr><tr><td colspan=\"7\">The purpose of this paper is to propose a</td></tr><tr><td colspan=\"7\">proper treatment of syntax and semantics in</td></tr><tr><td colspan=\"2\">machine</td><td colspan=\"3\">translation</td><td/><td>systems</td><td>from a heuristic</td></tr><tr><td colspan=\"3\">viewpoint,</td><td colspan=\"2\">together</td><td/><td>with</td><td>persuasive</td><td>examples</td></tr><tr><td colspan=\"2\">obtained</td><td colspan=\"3\">through</td><td colspan=\"2\">operating</td><td>experiences.</td><td>A</td></tr><tr><td colspan=\"3\">sub-language</td><td colspan=\"3\">approach</td><td>which</td><td>would</td><td>put</td><td>some</td></tr><tr><td colspan=\"7\">moderate restrictions on the syntax and semantics</td></tr><tr><td colspan=\"7\">of source language is also discussed.</td></tr></table>", |
| "html": null, |
| "text": "The second but intractable problem is that,", |
| "num": null, |
| "type_str": "table" |
| }, |
| "TABREF2": { |
| "content": "<table><tr><td/><td colspan=\"2\">Table 1 Dependency Pattern of Verb</td><td/><td/><td/><td/></tr><tr><td>Code</td><td>Verb Pattern</td><td>Examples</td><td/><td/><td/><td/></tr><tr><td>Vl</td><td>Be + ...</td><td>be</td><td/><td/><td/><td/></tr><tr><td>V2</td><td>Vi (# Be) + Complement,</td><td>get, look</td><td/><td/><td/><td/></tr><tr><td/><td>It/There + Vi + ...</td><td/><td/><td/><td/><td/></tr><tr><td>V3</td><td>Vi [+ Adverbial Modifier]</td><td>rise~ walk</td><td/><td/><td/><td/></tr><tr><td>V6</td><td>Vt + To-infinitive</td><td>intend</td><td/><td/><td/><td/></tr><tr><td>V7</td><td>Vt + Object</td><td>begin~ yield</td><td/><td/><td/><td/></tr><tr><td>V8</td><td>vt + that + ...</td><td>agree, think</td><td/><td/><td/><td/></tr><tr><td>V14</td><td>Vt + Object [+not] +</td><td>know, bring</td><td/><td/><td/><td/></tr><tr><td/><td>To-infinitive</td><td/><td/><td/><td/><td/></tr><tr><td>Code</td><td/><td/><td/><td/><td/><td/></tr><tr><td>SUBJ</td><td/><td/><td/><td/><td/><td/></tr><tr><td>OK/</td><td/><td/><td/><td/><td/><td/></tr><tr><td>TOOBJ</td><td/><td/><td/><td/><td/><td/></tr><tr><td>NAPP</td><td/><td/><td/><td/><td/><td/></tr><tr><td>GOV</td><td/><td/><td/><td/><td/><td/></tr><tr><td>TOGOV</td><td/><td/><td/><td/><td/><td/></tr><tr><td>ENGOV</td><td/><td/><td/><td/><td/><td/></tr><tr><td>ADJV</td><td/><td/><td/><td/><td/><td/></tr><tr><td>ENADj</td><td/><td/><td/><td/><td/><td/></tr><tr><td>ADVL</td><td/><td/><td/><td/><td/><td/></tr><tr><td>SENT</td><td/><td/><td/><td/><td/><td/></tr><tr><td/><td/><td/><td/><td/><td/><td/><td>An</td></tr><tr><td/><td/><td>example</td><td>of</td><td colspan=\"2\">top-down</td><td colspan=\"2\">operation</td><td>would</td><td>be</td><td>the</td></tr><tr><td/><td/><td colspan=\"6\">segmentation of an input sentence (i.e. the</td></tr><tr><td/><td/><td colspan=\"6\">sequence of word elements (WE's)) to get phrasal</td></tr><tr><td/><td/><td>elements</td><td colspan=\"2\">(PE),</td><td>and</td><td>an</td><td>example</td><td>of</td><td>bottom-up</td></tr><tr><td/><td/><td colspan=\"6\">operation would be the construction of tree-forms</td></tr><tr><td/><td/><td colspan=\"6\">or link-forms to get clausal elements (CE) or a</td></tr><tr><td/><td/><td colspan=\"6\">sentence (SE). These operations are supported by</td></tr><tr><td/><td/><td>syntax</td><td colspan=\"2\">directed</td><td colspan=\"3\">grammatical</td><td>data</td><td>such</td><td>as</td></tr><tr><td/><td/><td colspan=\"6\">verb dependency type codes (cf. Table i, which is</td></tr><tr><td/><td/><td colspan=\"6\">a simplified version of Hornby's classification</td></tr><tr><td/><td/><td colspan=\"6\">[5]), syntactic role codes (Table 2) and some</td></tr><tr><td/><td/><td colspan=\"6\">production rule type grammars (Table 3 & Table</td></tr><tr><td/><td/><td>4).</td><td/><td/><td/><td/></tr><tr><td/><td/><td colspan=\"6\">parts are already well-elaborated (cf. [i],</td><td>[8],</td></tr><tr><td/><td/><td colspan=\"2\">[ii], [12]).</td><td/><td/><td/></tr></table>", |
| "html": null, |
| "text": "HPM parser operates both in a top-down way globally and in a bottom-up way locally.It may be permissible to say that all these syntactic data are fairly compact and the kernel", |
| "num": null, |
| "type_str": "table" |
| }, |
| "TABREF3": { |
| "content": "<table><tr><td>(3) (4) In</td><td>order</td><td>to</td><td>boost</td><td>the</td><td colspan=\"2\">aforementioned</td></tr><tr><td colspan=\"2\">disambiguation</td><td>power,</td><td>it</td><td colspan=\"2\">is useful</td><td>to apply</td></tr><tr><td colspan=\"5\">semantic filters that facilitate</td><td colspan=\"2\">the selective</td></tr><tr><td colspan=\"7\">restrictions on linking a verb with nominals and</td></tr><tr><td colspan=\"5\">on linking a modifier with its head.</td><td/></tr><tr><td>Syntactic Roles</td><td/><td/><td/><td/><td/></tr><tr><td>Role</td><td/><td/><td/><td/><td/></tr><tr><td>Subject</td><td/><td/><td/><td/><td/></tr><tr><td>Object</td><td/><td/><td/><td/><td/></tr><tr><td>Object in To-infinitive Form</td><td/><td/><td/><td/><td/></tr><tr><td>Noun in Apposition</td><td/><td/><td/><td/><td/></tr><tr><td>Governing Verb</td><td/><td/><td/><td/><td/></tr><tr><td>Governing Verb in To-infinitive Form</td><td/><td/><td/><td/><td/></tr><tr><td>Governing Verb in Past Participle Form</td><td/><td/><td/><td/><td/></tr><tr><td>Adjectival</td><td/><td/><td/><td/><td/></tr><tr><td>Adjectival in Past Participle Form</td><td/><td/><td/><td/><td/></tr><tr><td>Adverbial</td><td/><td/><td/><td/><td/></tr><tr><td>Sentence</td><td/><td/><td/><td/><td/></tr></table>", |
| "html": null, |
| "text": "The weak point of syntax directed processors is their insufficient ability to disambiguate; i.e. the ability to identify dependency types of verb phrases and the ability to determine heads of prepositional phrase modifiers.", |
| "num": null, |
| "type_str": "table" |
| }, |
| "TABREF4": { |
| "content": "<table><tr><td colspan=\"2\">Pattern to be Scanned</td><td/><td colspan=\"2\">New Pattern to be Generated</td></tr><tr><td/><td/><td/><td>TOGOV~</td><td>+ OBJ</td></tr><tr><td>*: focus,</td><td>--: not mentioned,</td><td>~: empty,</td><td colspan=\"2\">[...]: optional</td></tr><tr><td/><td colspan=\"4\">Table 4 Rules for Constructing Clausal Elements</td></tr><tr><td colspan=\"2\">Pattern to be Scanned</td><td/><td colspan=\"2\">New Element to be Generated</td></tr><tr><td/><td>I*</td><td/><td>[ SENT |</td></tr></table>", |
| "html": null, |
| "text": "Rules for Assigning Syntactic Roles to Phrasal Elements", |
| "num": null, |
| "type_str": "table" |
| }, |
| "TABREF6": { |
| "content": "<table><tr><td/><td colspan=\"2\">Rules for Selecting</td></tr><tr><td/><td colspan=\"2\">Postpositions for \"in + N\"</td></tr><tr><td>Semantic</td><td>Japanese Post-</td><td/></tr><tr><td>Category of N</td><td>positions for ADVL/ADJV</td><td>English Examples</td></tr><tr><td colspan=\"2\">in+Nl (NlfPlace) Nl+de/Nl+niokeru</td><td>in California</td></tr><tr><td colspan=\"2\">in+N3 (N3=Time) N3+ni/N3+no</td><td>in Spring</td></tr><tr><td>in+N3&N4</td><td>--/N3&Nd+go-ni</td><td>in two days</td></tr><tr><td>(Nd=Quantit~)</td><td/><td/></tr><tr><td>in+N6</td><td>N6\u00f7dewa/N6+no</td><td>in my opinion</td></tr><tr><td>(N6fAbstract</td><td/><td/></tr><tr><td>Concept)</td><td/><td/></tr><tr><td colspan=\"2\">in+N8 (N8ffiMeans) NS+de/NS+niyoru</td><td>in Z-method</td></tr><tr><td>\u2022 No rules.</td><td>+de/+no</td><td>(speak) in English</td></tr><tr><td>\u2022 A kind of</td><td>+wo-kite/</td><td>in uniform</td></tr><tr><td>idiom [7] to</td><td>+wo-kita</td><td/></tr><tr><td>be retrieved</td><td>+wo-kakete/</td><td>in spectacles</td></tr><tr><td colspan=\"2\">directly from +wo-kaketa</td><td/></tr><tr><td>a lexicon.</td><td/><td/></tr><tr><td colspan=\"3\">(i0) To get back to the previous findings (I)</td></tr><tr><td>and</td><td/><td/></tr></table>", |
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| "num": null, |
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| "TABREF9": { |
| "content": "<table><tr><td/><td colspan=\"2\">Case Markers for CDD (subset only)</td></tr><tr><td colspan=\"2\">Predicative A</td><td>Agent</td></tr><tr><td>Dominance</td><td>0</td><td>Object</td></tr><tr><td colspan=\"2\">(Compulsory) C</td><td>Complement</td></tr><tr><td/><td>R</td><td>Recipient</td></tr><tr><td/><td colspan=\"2\">AC Agent in Causative</td></tr><tr><td/><td>T</td><td>Theme, Topic (Mental Subject)</td></tr><tr><td/><td>P</td><td>Partner</td></tr><tr><td/><td>Q</td><td>Quote</td></tr><tr><td/><td colspan=\"2\">RI Range of Interest</td></tr><tr><td/><td colspan=\"2\">RQ Range of Qualification</td></tr><tr><td/><td colspan=\"2\">RM Range of Mention</td></tr><tr><td/><td>I</td><td>Instrument</td></tr><tr><td/><td>E</td><td>Element</td></tr><tr><td>Adverbial</td><td colspan=\"2\">CT Goal in Abstract Collection</td></tr><tr><td colspan=\"3\">Modification CF Source in Abstract Collection</td></tr><tr><td>(Optional)</td><td colspan=\"2\">TP Point in Time</td></tr><tr><td>Adjective</td><td colspan=\"2\">ET Embedding Sentence Type Modifier</td></tr><tr><td>Modification</td><td/><td>whose gapping is Theme</td></tr><tr><td>(Optional)</td><td>EA</td><td>whose gapping is Agent</td></tr><tr><td/><td>EO</td><td>whose gapping is Object</td></tr><tr><td>Link and</td><td/><td/></tr></table>", |
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| "TABREF10": { |
| "content": "<table><tr><td/><td>Classification of Optional Case</td></tr><tr><td/><td>Markers for Modification (subset only)</td></tr><tr><td colspan=\"2\">Phase Code Most-Likely Prepositions or Participles</td></tr><tr><td>F</td><td>from</td></tr><tr><td>T</td><td>to, till</td></tr><tr><td>D</td><td>during</td></tr><tr><td>P</td><td>at</td></tr><tr><td>I</td><td>in, inside</td></tr><tr><td>O</td><td>out, outside</td></tr><tr><td>V</td><td>over, above</td></tr><tr><td>U</td><td>under, below</td></tr><tr><td>S</td><td>beside</td></tr><tr><td>B</td><td>before, in front of</td></tr><tr><td>A</td><td>after, behind</td></tr><tr><td>AL</td><td>along</td></tr><tr><td>H</td><td>through</td></tr><tr><td>AB</td><td>over, superior to</td></tr><tr><td>SE</td><td>apart from</td></tr><tr><td>WI</td><td>within</td></tr><tr><td>\u2022..</td><td/></tr><tr><td colspan=\"2\">. Case Marker E Body Code + Phase Code</td></tr><tr><td colspan=\"2\">\u2022 Body Code ~ T (=Time)IS (=Space)IC (=Collection)</td></tr></table>", |
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| } |
| } |
| } |
