Abstract
In this work, a data-driven approach for extracting answers from web-snippets is presented. Answers are identified by matching contextual distributional patterns of the expected answer type(EAT) and answer candidates. These distributional patterns are directly learnt from previously annotated tuples {question, sentence, answer}, and the learning mechanism is based on the principles language acquisition. Results shows that this linguistic motivated data-driven approach is encouraging.
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Figueroa, A., Atkinson, J. (2006). Using Syntactic Distributional Patterns for Data-Driven Answer Extraction from the Web. In: Gelbukh, A., Reyes-Garcia, C.A. (eds) MICAI 2006: Advances in Artificial Intelligence. MICAI 2006. Lecture Notes in Computer Science(), vol 4293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925231_94
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DOI: https://doi.org/10.1007/11925231_94
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49026-5
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