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QNP Textual Entailment with Polynomial Event Semantics

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New Frontiers in Artificial Intelligence (JSAI-isAI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13856))

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Abstract

FraCaS textual entailment corpus has become the standard benchmark for semantics theories, in particular, theories of quantification (Sect. 1 of FraCaS). Here we apply it to polynomial event semantics: the latest approach to combining quantification and Neo-Davidsonian event semantics, maintaining compositionality and the in situ analysis of quantifiers. Although several FraCaS problems look custom-made for the polynomial events semantics, there are challenges: the variety of generalized quantifiers (including ‘many’, ‘most’ and ‘few’); copula, existence, and relative clauses. We address them in this paper.

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Notes

  1. 1.

    (3) shows how the denotations are supposed to be parenthesized. We drop the parentheses from now on.

  2. 2.

    More generally, definite descriptions can analyzed as \(\mathcal {I}\) \(\textsf{Survey}\), see Sect. 3. Our example works either way, so we proceed with the simpler analysis.

  3. 3.

    We suppose there are thematic functions \(\mathsf {occursAt'}\) and \(\mathsf {deadline'}\). that tell the time of occurrence and the deadline, resp., for an event. Then \(\textsf{onTime} = \{ e \mid \mathsf {occursAt'}\!(e) \le \mathsf {deadline'}\!(e)\}\). One may analyze ‘on time’ differently (e.g., with the deadline being taken from the context). However, that does not matter for entailment, which is decided for our example solely from the property of \(\sqcap \), see (5).

  4. 4.

    By group, here and in the following, we mean any unorderded collection: something like a roster.

  5. 5.

    One may hence say that a concept is a set of atoms – however, we never mix individuals and event sets in the same set.

References

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Acknowledgments

We are very grateful to the reviewers and Daisuke Bekki for their insightful comments and questions. This work was partially supported by a JSPS KAKENHI Grant Number 17K00091.

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Authors and Affiliations

  1. Tohoku University, Sendai, Japan

    Oleg Kiselyov & Haruki Watanabe

Authors
  1. Oleg Kiselyov
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  2. Haruki Watanabe
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Correspondence to Oleg Kiselyov .

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Editors and Affiliations

  1. Kansai University, Suita, Japan

    Katsutoshi Yada

  2. Tokyo Metropolitan University, Tokyo, Japan

    Yasufumi Takama

  3. Keio University, Tokyo, Japan

    Koji Mineshima

  4. National Institute of Informatics, Tokyo, Japan

    Ken Satoh

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Kiselyov, O., Watanabe, H. (2023). QNP Textual Entailment with Polynomial Event Semantics. In: Yada, K., Takama, Y., Mineshima, K., Satoh, K. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2021. Lecture Notes in Computer Science(), vol 13856. Springer, Cham. https://doi.org/10.1007/978-3-031-36190-6_14

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  • DOI: https://doi.org/10.1007/978-3-031-36190-6_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36189-0

  • Online ISBN: 978-3-031-36190-6

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