PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Towards a Probabilistic Model for Lexical Entailment
Eyal Shnarch, Jacob Goldberger and Ido Dagan
In: TextInfer 2011 Workshop on Textual Entailment, 30 July 2011, Edinburgh, Scotland, UK.

Abstract

While modeling entailment at the lexical-level is a prominent task, addressed by most textual entailment systems, it has been approached mostly by heuristic methods, neglecting some of its important aspects. We present a probabilistic approach for this task which covers aspects such as differentiating various resources by their reliability levels, considering the length of the entailed sentence, the number of its covered terms and the existence of multiple evidence for the entailment of a term. The impact of our model components is validated by evaluations, which also show that its performance is in line with the best published entailment systems.

EPrint Type:Conference or Workshop Item (Paper)
Additional Information:An extension to an ACL 2011 short paper
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:8841
Deposited By:Eyal Shnarch
Deposited On:21 February 2012