Named Entity Recognition and Named Entity Linking on Esports Contents
Ziyu Liu, Yifan Leng, Meiqi Wang, Congzhu Lin
DOI: http://dx.doi.org/10.15439/2020F24
Citation: Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 21, pages 189–192 (2020)
Abstract. We built a named entity recognition/linking system on Esports News. We established an ontology for Esports-related entities, collected and annotated corpus from 80 articles on 4 different Esports titles, trained CRF and BERT-based entity recognizer, built a basic Dota2 knowledge base and a Entity linker that links mentions to articles in Liquipedia, and an end-to-end web app which serves as a demo of this entire proof-of-conecpt system. Our system achieved an over 61\% overall entity-level F1-score on the test set for the NER task, and also satisfying intuitive results on the linking task.
References
- N. Chinchor and P. Robinson, “Muc-7 named entity task definition,” in Proceedings of the 7th Conference on Message Understanding, vol. 29, 1997, pp. 1–21.
- D. Rao, P. McNamee, and M. Dredze, “Entity linking: Finding extracted entities in a knowledge base,” in Multi-source, multilingual information extraction and summarization. Springer, 2013, pp. 93–115.
- T. Yao, W. Ding, and G. Erbach, “Chiners: a chinese named entity recognition system for the sports domain,” in Proceedings of the second SIGHAN workshop on Chinese language processing, 2003, pp. 55–62.
- C.-K. Lee and M.-G. Jang, “Named entity recognition with structural svms and pegasos algorithm,” Korean Journal of Cognitive Science, vol. 21, no. 4, pp. 655–667, 2010.
- X. Seti, A. Wumaier, T. Yibulayin, D. Paerhati, L. Wang, and A. Saimaiti, “Named-entity recognition in sports field based on a character-level graph convolutional network,” Information, vol. 11, no. 1, p. 30, 2020.
- J. Lafferty, A. McCallum, and F. C. Pereira, “Conditional random fields: Probabilistic models for segmenting and labeling sequence data,” 2001.
- J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “Bert: Pre-training of deep bidirectional transformers for language understanding,” arXiv preprint https://arxiv.org/abs/1810.04805, 2018.