Adding semantics to data-driven paraphrasing

We add an interpretable semantics to the paraphrase database (PPDB). To date, the relationship between the phrase pairs in the database has been weakly defined as approximately equivalent. We show that in fact these pairs represent a vari-ety of relations, including directed entail-ment (little girl/girl) and exclusion (no-body/someone). We automatically assign semantic entailment relations to entries in PPDB using features derived from past work on discovering inference rules from text and semantic taxonomy induction. We demonstrate that our model assigns these entailment relations with high accuracy. In a downstream RTE task, our labels rival relations from WordNet and improve the coverage of a proof-based RTE system by 17%.