Abstract
Discourse structure analysis is an important task in Natural Language Processing (NLP) and it is helpful to many NLP tasks, such as automatic summarization and information extraction. However, there are only a few researches on Chinese macro discourse structure analysis due to the lack of annotated corpora. In this paper, combining structure recognition with nuclearity recognition, we propose a Label Degeneracy Combination Model (LD-CM) to find the solution of structure recognition in the solution space of nuclearity recognition. Experimental results on the Macro Chinese Discourse TreeBank (MCDTB) show that our model improves the accuracy by 1.21%, compared with the baseline system.
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Acknowledgments
The authors would like to thank three anonymous reviewers for their comments on this paper. This research was supported by the National Natural Science Foundation of China under Grant Nos. 61772354, 61773276 and 61472265, and was also supported by the Strategic Pioneer Research Projects of Defense Science and Technology under Grant No. 17-ZLXDXX-02-06-02-04.
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Jiang, F., Li, P., Chu, X., Zhu, Q., Zhou, G. (2018). Recognizing Macro Chinese Discourse Structure on Label Degeneracy Combination Model. In: Zhang, M., Ng, V., Zhao, D., Li, S., Zan, H. (eds) Natural Language Processing and Chinese Computing. NLPCC 2018. Lecture Notes in Computer Science(), vol 11109. Springer, Cham. https://doi.org/10.1007/978-3-319-99501-4_8
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