Paraphrase identification with lexico-syntactic graph subsumption


The paper presents a new approach to the problem of paraphrase identification. The new approach extends a previously proposed method for the task of textual entailment. The relationship between paraphrases and entailment is discussed to theoretically justify the new approach. The proposed approach is useful because it uses relatively few resources compared to similar systems yet it produces results similar or better than other approaches to paraphrase identification. The approach also offers significantly better results than two baselines. We report results on a standard data set as well as on a new, balanced data set. Copyright © 2008, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Publication Title

Proceedings of the 21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21

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