Textual Entailment

Sebastian Pado, Ido Dagan

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Textual entailment is a binary relation between two natural-language texts (called ‘text’ and ‘hypothesis’), where readers of the ‘text’ would agree the ‘hypothesis’ is most likely true (Peter is snoring → A man sleeps). Its recognition requires an account of linguistic variability ( an event may be realized in different ways, e.g. Peter buys the car ↔ The car is purchased by Peter) and of relationships between events (e.g. Peter buys the car → Peter owns the car). Unlike logics-based inference, textual entailment also covers cases of probable but still defeasible entailment (A hurricane hit Peter’s town → Peter’s town was damaged). Since human common-sense reasoning often involves such defeasible inferences, textual entailment is of considerable interest for real-world language processing tasks, as a generic, application-independent framework for semantic inference. This chapter discusses the history of textual entailment, approaches to recognizing it, and its integration in various NLP tasks.
Original languageAmerican English
Title of host publicationThe Oxford Handbook of Computational Linguistics 2nd edition
EditorsRuslan Mitkov
PublisherOxford University Press Oxford
Pages151-170
Number of pages20
Edition2nd
ISBN (Electronic)9780199573691
DOIs
StatePublished - 2016

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