Adding context to semantic data-driven paraphrasing

Vered Shwartz, Ido Dagan

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

4 Scopus citations

Abstract

Recognizing lexical inferences between pairs of terms is a common task in NLP applications, which should typically be performed within a given context. Such context-sensitive inferences have to consider both term meaning in context as well as the fine-grained relation holding between the terms. Hence, to develop suitable lexical inference methods, we need datasets that are annotated with fine-grained semantic relations in-context. Since existing datasets either provide outof- context annotations or refer to coarsegrained relations, we propose a methodology for adding context-sensitive annotations. We demonstrate our methodology by applying it to phrase pairs from PPDB 2.0, creating a novel dataset of finegrained lexical inferences in-context and showing its utility in developing contextsensitive methods.

Original languageEnglish
Title of host publication*SEM 2016 - 5th Joint Conference on Lexical and Computational Semantics, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages108-113
Number of pages6
ISBN (Electronic)9781941643921
DOIs
StatePublished - 2016
Event5th Joint Conference on Lexical and Computational Semantics, *SEM 2016 - Berlin, Germany
Duration: 11 Aug 201612 Aug 2016

Publication series

Name*SEM 2016 - 5th Joint Conference on Lexical and Computational Semantics, Proceedings

Conference

Conference5th Joint Conference on Lexical and Computational Semantics, *SEM 2016
Country/TerritoryGermany
CityBerlin
Period11/08/1612/08/16

Bibliographical note

Funding Information:
This work was partially supported by an Intel ICRI-CI grant, the Israel Science Foundation grant 880/12, and the German Research Foundation through the German-Israeli Project Cooperation (DIP, grant DA 1600/1-1).

Funding

This work was partially supported by an Intel ICRI-CI grant, the Israel Science Foundation grant 880/12, and the German Research Foundation through the German-Israeli Project Cooperation (DIP, grant DA 1600/1-1).

FundersFunder number
DIPDA 1600/1-1
German-Israeli Project Cooperation
Intel ICRI-CI
Deutsche Forschungsgemeinschaft
Israel Science Foundation880/12

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