Learning dictionaries for information extraction by multi-level bootstrapping
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Since paraphrasing is one of the crucial tasks in natural language understanding and generation, this paper introduces a novel technique to extract paraphrases for emotion terms, from non-parallel corpora. We present a bootstrapping technique for identifying paraphrases, starting with a small number of seeds. WordNet Affect emotion words are used as seeds. The bootstrapping approach learns extraction patterns for six classes of emotions. We use annotated blogs and other datasets as texts from which to extract paraphrases, based on the highest-scoring extraction patterns. The results include lexical and morpho-syntactic paraphrases, that we evaluate with human judges.