Paper: Discourse Complements Lexical Semantics for Non-factoid Answer Reranking

ACL ID P14-1092
Title Discourse Complements Lexical Semantics for Non-factoid Answer Reranking
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

We propose a robust answer reranking model for non-factoid questions that inte- grates lexical semantics with discourse in- formation, driven by two representations of discourse: a shallow representation cen- tered around discourse markers, and a deep one based on Rhetorical Structure Theory. We evaluate the proposed model on two corpora from different genres and domains: one from Yahoo! Answers and one from the biology domain, and two types of non-factoid questions: manner and reason. We experimentally demon- strate that the discourse structure of non- factoid answers provides information that is complementary to lexical semantic sim- ilarity between question and answer, im- proving performance up to 24% (relative) over a state-of-the-art model that exploits lexical semantic similarity al...