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NAACL
2010

Tree Edit Models for Recognizing Textual Entailments, Paraphrases, and Answers to Questions

8 years 4 months ago
Tree Edit Models for Recognizing Textual Entailments, Paraphrases, and Answers to Questions
We describe tree edit models for representing sequences of tree transformations involving complex reordering phenomena and demonstrate that they offer a simple, intuitive, and effective method for modeling pairs of semantically related sentences. To efficiently extract sequences of edits, we employ a tree kernel as a heuristic in a greedy search routine. We describe a logistic regression model that uses 33 syntactic features of edit sequences to classify the sentence pairs. The approach leads to competitive performance in recognizing textual entailment, paraphrase identification, and answer selection for question answering.
Michael Heilman, Noah A. Smith
Added 14 Feb 2011
Updated 14 Feb 2011
Type Journal
Year 2010
Where NAACL
Authors Michael Heilman, Noah A. Smith
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