Paper: Lexical Inference over Multi-Word Predicates: A Distributional Approach

ACL ID P14-1061
Title Lexical Inference over Multi-Word Predicates: A Distributional Approach
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Representing predicates in terms of their argument distribution is common practice in NLP. Multi-word predicates (MWPs) in this context are often either disregarded or considered as fixed expressions. The lat- ter treatment is unsatisfactory in two ways: (1) identifying MWPs is notoriously diffi- cult, (2) MWPs show varying degrees of compositionality and could benefit from taking into account the identity of their component parts. We propose a novel approach that integrates the distributional representation of multiple sub-sets of the MWP?s words. We assume a latent distri- bution over sub-sets of the MWP, and esti- mate it relative to a downstream prediction task. Focusing on the supervised identi- fication of lexical inference relations, we compare against state-of-the-art baselines tha...