Exact decoding for jointly labeling and chunking sequences

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Abstract

There are two decoding algorithms essential to the area of natural language processing. One is the Viterbi algorithm for linear-chain models, such as HMMs or CRFs. The other is the CKY algorithm for probabilistic context free grammars. However, tasks such as noun phrase chunking and relation extraction seem to fall between the two, neither of them being the best fit. Ideally we would like to model entities and relations, with two layers of labels. We present a tractable algorithm for exact inference over two layers of labels and chunks with time complexity O(n2), and provide empirical results comparing our model with linear-chain models.

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Shimizu, N., & Haas, A. (2006). Exact decoding for jointly labeling and chunking sequences. In COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Main Conference Poster Sessions (pp. 763–770). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1273073.1273171

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