MIPA: Mutual Information Based Paraphrase Acquisition via Bilingual Pivoting

We present a pointwise mutual information (PMI) based approach for formalizing paraphrasability and propose a variant of PMI, called mutual information based paraphrase acquisition (MIPA), for paraphrase acquisition. Our paraphrase acquisition method first acquires lexical paraphrase pairs by bilingual pivoting and then reranks them by PMI and distributional similarity. The complementary nature of information from bilingual corpora and frommonolingual corpora renders the proposed method robust. Experimental results show that the proposed method substantially outperforms bilingual pivoting and distributional similarity themselves in terms of metrics such as mean reciprocal rank, mean average precision, coverage, and Spearman’s correlation.