mlsanityData to 7 Oct 2026

Blindness to Modality Helps Entailment Graph Mining

arXiv 2109.10227 ↗First posted 21 Sep 2021cs.CLcited by 2

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Abstract (arXiv)

Understanding linguistic modality is widely seen as important for downstream tasks such as Question Answering and Knowledge Graph Population. Entailment Graph learning might also be expected to benefit from attention to modality. We build Entailment Graphs using a news corpus filtered with a modality parser, and show that stripping modal modifiers from predicates in fact increases performance. This suggests that for some tasks, the pragmatics of modal modification of predicates allows them to contribute as evidence of entailment.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 6 of its 44 references that are in the map. First posted on arXiv 21 Sep 2021.

Builds on

6 of 44 references.

References · 6

  1. 2019Probabilistic Models of Relational Implicationcited by 17
  2. 2021Multivalent Entailment Graphs for Question Answeringcited by 10
  3. 2016Exploring Different Dimensions of Attention for Uncertainty Detectioncited by 7
  4. 2021Incorporating Temporal Information in Entailment Graph Miningcited by 7
  5. 2021Modality and Negation in Event Extractioncited by 6
  6. 2014A Modality Lexicon and its use in Automatic Taggingcited by 4

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Citing papers per year: 2022: 2.

2 papers.