Focused entailment graphs for open IE propositions

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Open IE methods extract structured propositions from text. However, these propositions are neither consolidated nor generalized, and querying them may lead to insufficient or redundant information. This work suggests an approach to organize open IE propositions using entailment graphs. The entailment relation unifies equivalent propositions and induces a specific-to-general structure. We create a large dataset of gold-standard proposition entailment graphs, and provide a novel algorithm for automatically constructing them. Our analysis shows that predicate entailment is extremely context-sensitive, and that current lexical-semantic resources do not capture many of the lexical inferences induced by proposition entailment.

Original languageEnglish
Title of host publicationCoNLL 2014 - 18th Conference on Computational Natural Language Learning, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages87-97
Number of pages11
ISBN (Electronic)9781941643020
DOIs
StatePublished - 2014
Event18th Conference on Computational Natural Language Learning, CoNLL 2014 - Baltimore, United States
Duration: 26 Jun 201427 Jun 2014

Publication series

NameCoNLL 2014 - 18th Conference on Computational Natural Language Learning, Proceedings

Conference

Conference18th Conference on Computational Natural Language Learning, CoNLL 2014
Country/TerritoryUnited States
CityBaltimore
Period26/06/1427/06/14

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Artificial Intelligence
  • Linguistics and Language

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