Textual entailment graphs

Lili Kotlerman, Ido Dagan, Bernardo Magnini, Luisa Bentivogli

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

In this work, we present a novel type of graphs for natural language processing (NLP), namely textual entailment graphs (TEGs). We describe the complete methodology we developed for the construction of such graphs and provide some baselines for this task by evaluating relevant state-of-the-art technology. We situate our research in the context of text exploration, since it was motivated by joint work with industrial partners in the text analytics area. Accordingly, we present our motivating scenario and the first gold-standard dataset of TEGs. However, while our own motivation and the dataset focus on the text exploration setting, we suggest that TEGs can have different usages and suggest that automatic creation of such graphs is an interesting task for the community.

Original languageEnglish
Pages (from-to)699-724
Number of pages26
JournalNatural Language Engineering
Volume21
Issue number5
DOIs
StatePublished - 1 Nov 2015

Bibliographical note

Publisher Copyright:
Copyright © Cambridge University Press 2015.

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