PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Semantic inference at the lexical-syntactic level
Roy Bar Haim, Ido Dagan, Iddo Greental and Eyal Shnarch
In: AAAI 2007, 22 Jul - 26 Jul 2007, Vancouver, Canada.

Abstract

Semantic inference is an important component in many natural language understanding applications. Classical approaches to semantic inference rely on complex logical representations. However, practical applications usually adopt shallower lexical or lexical-syntactic representations, but lack a principled inference framework. We propose a generic semantic inference framework that operates directly on syntactic trees. New trees are inferred by applying entailment rules, which provide a unified representation for varying types of inferences. Rules were generated by manual and automatic methods, covering generic linguistic structures as well as specific lexical-based inferences. Initial empirical evaluation in a Relation Extraction setting support the validity of our approach.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:3439
Deposited By:Roy Bar Haim
Deposited On:11 February 2008