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ABSTRACT
There are a great number of complex relations among different characters in an opera. Retrieving such relations is crucial for performers and audience to accurately understand the features and behaviour of roles. Aiming to automatically extract relations among characters in an opera, in this paper we propose an effective method that can extract character relations from opera scripts. Firstly, we construct a uniform reasoning framework for opera scripts. Based on this model, we propose a deep syntax-parsing method to detect character relations from opera scripts. After that, we propose a new deep learning approach called SL-Bi-LSTM-CRF to extract the objects involved in character relations. The proposed SL-Bi-LSTM-CRF algorithm is a sentence-level relation extraction algorithm based on the Bi-directional LSTM with a CRF layer. With this mechanism, we are able to get a detailed description for character relations. We conduct experiments on a real dataset of opera scripts. The experimental results in terms of precision, recall, and F-score suggest the effectiveness of our proposal.
Acknowledgements
We would like to thank the editors and anonymous reviewers for their valuable suggestions and comments to improve the quality of the paper. This work is partially supported by the Humanities and Social Sciences Foundation of the Ministry of Education (No. 17YJCZH260), the CERNET Innovation Project (No. NGII20180403), and the National Science Foundation of China (No. 61672479).
Disclosure statement
No potential conflict of interest was reported by the authors.