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Automatically Extracting Templates from Examples for NLP Tasks
2008
Pacific Asia Conference on Language, Information and Computation
In this paper, we present the approaches used by our NLP systems to automatically extract templates for example-based machine translation and pun generation. Our translation system is able to extract an average of 73.25% correct translation templates, resulting in a translation quality that has a low word error rate of 18% when the test document contains sentence patterns matching the training set, to a high 85% when the test document is different from the training corpus. Our pun generator is
dblp:conf/paclic/OngHN08
fatcat:qnah2rwvdzgdxhqng72tjjc4ma