Abstract
We present an alignment-based approach to semi-supervised relation extraction task including more than two arguments. We concentrate on improving not only the precision of the extracted result, but also on the coverage of the method. Our relation extraction method is based on an alignment-based pattern matching approach which provides more flexibility of the method. In addition, we extract all relationships including two or more arguments at once in order to obtain the integrated result with high quality. We present experimental results which indicate the effectiveness of our method.
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© 2008 Springer-Verlag Berlin Heidelberg
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Kim, S., Jeong, M., Lee, G.G., Ko, K., Lee, Z. (2008). An Alignment-Based Approach to Semi-supervised Relation Extraction Including Multiple Arguments. In: Li, H., Liu, T., Ma, WY., Sakai, T., Wong, KF., Zhou, G. (eds) Information Retrieval Technology. AIRS 2008. Lecture Notes in Computer Science, vol 4993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68636-1_59
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DOI: https://doi.org/10.1007/978-3-540-68636-1_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68633-0
Online ISBN: 978-3-540-68636-1
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