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

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.