人工知能
Online ISSN : 2435-8614
Print ISSN : 2188-2266
人工知能学会誌(1986~2013, Print ISSN:0912-8085)
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徳永 健伸田中 穂積
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解説誌・一般情報誌 フリー

1991 年 6 巻 2 号 p. 228-235

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To improve the quality of machine translation systems, we should step toward the deeper analysis at the conceptual level. Developing the machine translation systems with deeper analysis requires the dictionaries including following information ; the set of conceptual items, the mapping relation between the surface words and the conceptual items, and the mapping relation between the conceptual items of the source language and that of the target language. There are several researches to compile such dictionaries. Japan Electronic Dictionary Research Institute (EDR) is now compiling such dictionaries on a large scale. Nirenburg, et al. at Carnegie Mellon University has proposed a systematic method to construct a conceptual dictionary. These attempts try to compile the dictionary by hand with the help of software tools. However this approach suffers from the problems such as huge amount of manual labor, the unstable result and so forth. Unlike this approach, the paper proposes a method to extract the information about the conceptual items from a pair of machine readable bilingual dictionaries in an automatic way. It is very difficult to compile the complete dictionary in a fully automatic way. The results of the method may require some refinement and modifications by human. Our goal is rather to automate the compilation process as much as possible and to decrease manual labor. In the paper, we make an approximation in that each word sense defined in the bilingual dictionary is considered as a conceptual item. Since each word sense has the proper translations in the bilingual dictionary, the above approximation is reasonable in terms of word choice in the translation, and we can easily get both the set of conceptual items and the mapping relation between the surface words and the conceptual items. The most difficult thing is to get the mapping relation between the conceptual items of the source language and that of the target language. The paper focuses on this issue. We introduce three types of translation circuits. The translation circuit is a tuple which consists of four elements, that is, a headword of both the languages and one of the word sense of both the headwords, with the condition that the word sense of one language should have the headword of the other language as a translation. We assume that the word senses in a translation circuit represent the same concept, that is, there is a mapping relation between the conceptual items (word sense) in a translation circuit. The paper describes the outline of a preliminary experiment conducted to verify this assumption. The results of the experiment are promising and some remarks are also given. We conclude the paper with pointing out the possibility by extending our method to construct the set of conceptual items which can be shared by more than two languages.

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© 1991 人工知能学会
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