A unified analysis of natural language inference based on the methods of proof theory and diagrammatic logic
| Project/Area Number |
17K13316
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Philosophy/Ethics
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| Research Institution | Keio University (2020)
Ochanomizu University (2017-2019) |
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Principal Investigator |
Mineshima Koji 慶應義塾大学, 文学部(三田), 准教授 (80725739)
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 形式意味論 / 論理学 / 証明論 / 自然言語推論 / 図形推論 / 型理論 / 計算言語学 / 含意関係認識 / 意味論 |
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| Outline of Final Research Achievements |
The aim of this research was to build a logical framework for analyzing natural language inferences in a way that is more in line with the structure of natural language, using the methods of proof theory in modern logic and diagrammatic logic. On the basis of a type-theoretic syntax (categorial grammar), I developed a compositional semantics and proof system for inferences with various linguistic phenomena in natural language. I also developed a method to apply this framework to the task of recognizing textual entailment in computational linguistics.
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| Academic Significance and Societal Importance of the Research Achievements |
人は自然言語を使っていともたやすく情報を伝達したり収集したりすることができる。しかし、その仕組みを理論的に解明することは決して容易なことではない。特に自然言語による推論は、言語の構造と意味、常識や世界知識、言葉が使用される文脈などさまざまな要因が関与した複雑な現象である。本研究ではこの研究に主に現代論理学の証明論の手法を用いて取り組んだ。特に文脈を考慮してさまざまな文の意味を合成的に導出し、自動推論を行う理論的な枠組み、またそれを計算言語学の含意関係認識の問題に応用する方法を発展させ、その成果を公開した。
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Report
(5 results)
Research Products
(33 results)
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[Journal Article] Neural sentence generation from formal semantics2018
Author(s)
Kana Manome, Masashi Yoshikawa, Hitomi Yanaka, Pascual Martinez-Gomez, Koji Mineshima and Daisuke Bekki
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Journal Title
Proceedings of the 11th International Conference on Natural Language Generation (INLG 2018)
Volume: 11
Pages: 408-414
Related Report
Peer Reviewed / Open Access
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