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Textual entailment graphs

Published online by Cambridge University Press:  23 June 2015

LILI KOTLERMAN ,
IDO DAGAN ,
BERNARDO MAGNINI  and
LUISA BENTIVOGLI
LILI KOTLERMAN
Affiliation:
Department of Computer Science, Bar-Ilan University, Ramat Gan, Israel e-mail: lili.dav@gmail.com, dagan@cs.biu.ac.il
IDO DAGAN
Affiliation:
Department of Computer Science, Bar-Ilan University, Ramat Gan, Israel e-mail: lili.dav@gmail.com, dagan@cs.biu.ac.il
BERNARDO MAGNINI
Affiliation:
Human Language Technologies Research Unit, Fondazione Bruno Kessler, Povo, Trento, Italy e-mail: magnini@fbk.eu, bentivo@fbk.eu
LUISA BENTIVOGLI
Affiliation:
Human Language Technologies Research Unit, Fondazione Bruno Kessler, Povo, Trento, Italy e-mail: magnini@fbk.eu, bentivo@fbk.eu
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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.

Type
Articles
Information
Natural Language Engineering , Volume 21 , Special Issue 5: Graphs in NLP , November 2015 , pp. 699 - 724
Copyright
Copyright © Cambridge University Press 2015 

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