Generating an entailment corpus from news headlines

28Citations
Citations of this article
78Readers
Mendeley users who have this article in their library.

Abstract

We describe our efforts to generate a large (100,000 instance) corpus of textual entailment pairs from the lead paragraph and headline of news articles. We manually inspected a small set of news stories in order to locate the most productive source of entailments, then built an annotation interface for rapid manual evaluation of further exemplars. With this training data we built an SVM-based document classifier, which we used for corpus refinement purposes-we believe that roughly three-quarters of the resulting corpus are genuine entailment pairs. We also discuss the difficulties inherent in manual entailment judgment, and suggest ways to ameliorate some of these.

Cite

CITATION STYLE

APA

Burger, J., & Ferro, L. (2005). Generating an entailment corpus from news headlines. In EMSEE 2005 - Empirical Modeling of Semantic Equivalence and Entailment@ACL 2005, Proceedings of the Workshop (pp. 49–54). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1631862.1631871

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free