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. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4993 LNCS, pp. 526–536). https://doi.org/10.1007/978-3-540-68636-1_59
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