Publication
ACL-IJCNLP 2015
Conference paper

Parsing paraphrases with joint inference

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Abstract

Treebanks are key resources for developing accurate statistical parsers. However, building treebanks is expensive and timeconsuming for humans. For domains requiring deep subject matter expertise such as law and medicine, treebanking is even more difficult. To reduce annotation costs for these domains, we develop methods to improve cross-domain parsing inference using paraphrases. Paraphrases are easier to obtain than full syntactic analyses as they do not require deep linguistic knowledge, only linguistic fluency. A sentence and its paraphrase may have similar syntactic structures, allowing their parses to mutually inform each other. We present several methods to incorporate paraphrase information by jointly parsing a sentence with its paraphrase. These methods are applied to state-of-The-Art constituency and dependency parsers and provide significant improvements across multiple domains.

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Publication

ACL-IJCNLP 2015

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