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Translate Japanese into Formal Languages with an Enhanced Generalization Algorithm

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Intelligent Computing (SAI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1229))

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Abstract

In this paper, we propose the extension of the semi-automated semantic parsing platform: NL2KR to Japanese. Japanese is an agglutinative language and it is difficult to assign the meaning of each word since different meanings are created using a single root-word. We introduce two algorithms, the Phrase Override and the enhanced Generalization. The Phrase Override algorithm gives the same feature of the original NL2KR: Syntax Override that adjusts the output Combinatory Categorial Grammar (CCG) Parse tree structure from its English CCG parser. To extend the other languages, however, it is needed to implement the CCG parser for the other languages. Japanese CCG Parser is provided, and the Phrase Override gives the way to adjust the generated CCG parse tree structure from the Japanese CCG parser. The Generalization used in NL2KR generates the meanings of missing words by applying missing words. Our proposing enhanced Generalization algorithm uses the semantically similar words of the missing word and apply the templates of these words to generate the missing word’s meanings. The evaluation result shows that this approach improves the accuracy of not only Japanese but also English with the smaller learned lexicons. For the evaluation, we provide new data corpora for Japanese. GeoQuery corpus is translated several languages including Japanese but the Japanese GeoQuery is a Japanese transliteration. We provide the Japanese translated GeoQuery and this is the first Japanese corpora. Our proposed approach can extend to other agglutinative languages such as Turkish, Finish, and Esperanto when a CCG parser is available for them. Our platform is Java base and it does not depends on the machine environment.

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Notes

  1. 1.

    goo.gl/MAj70v.

  2. 2.

    http://www.biology-questions-and-answers.com.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Arizona State University, Tempe, AZ, 85281, USA

    Kazuaki Kashihara

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  1. Kazuaki Kashihara
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Correspondence to Kazuaki Kashihara .

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Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Kashihara, K. (2020). Translate Japanese into Formal Languages with an Enhanced Generalization Algorithm. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1229. Springer, Cham. https://doi.org/10.1007/978-3-030-52246-9_47

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