Abstract
This paper focuses on recognizing person relations indicated by predicates from large scale of free texts. In order to determine whether a sentence contains a potential relation between persons, we cast this problem to a classification task. Dynamic Convolution Neural Network (DCNN) is improved for this task. It uses frame convolution for making uses of more features efficiently. Experimental results on Chinese person relation recognition show that the proposed model is superior when compared to the original DCNN and several strong baseline models. We also explore employing large scale unlabeled data to achieve further improvements.
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Liang, Z., Yuan, C., Leng, B., Wang, X. (2015). Recognition of Person Relation Indicated by Predicates. In: Li, J., Ji, H., Zhao, D., Feng, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2015. Lecture Notes in Computer Science(), vol 9362. Springer, Cham. https://doi.org/10.1007/978-3-319-25207-0_26
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DOI: https://doi.org/10.1007/978-3-319-25207-0_26
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