Paper: Semantic Neighborhoods as Hypergraphs

ACL ID P13-2040
Title Semantic Neighborhoods as Hypergraphs
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2013
Authors

Ambiguity preserving representations such as lattices are very useful in a num- ber of NLP tasks, including paraphrase generation, paraphrase recognition, and machine translation evaluation. Lattices compactly represent lexical variation, but word order variation leads to a combina- torial explosion of states. We advocate hypergraphs as compact representations for sets of utterances describing the same event or object. We present a method to construct hypergraphs from sets of utterances, and evaluate this method on a simple recognition task. Given a set of utterances that describe a single object or event, we construct such a hypergraph, and demonstrate that it can recognize novel descriptions of the same event with high accuracy.