Techniques for Jointly Extracting Entities and Relations: A Survey

Author:

Pawar Sachin,Bhattacharyya Pushpak,Palshikar Girish K.

Publisher

Springer Nature Switzerland

Reference28 articles.

1. Bekoulis, G., Deleu, J., Demeester, T., Develder, C.: Joint entity recognition and relation extraction as a multi-head selection problem. arXiv preprint arXiv:1804.07847 (2018)

2. Bunescu, R., Mooney, R.: A shortest path dependency kernel for relation extraction. In: Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, pp. 724–731. Association for Computational Linguistics, Vancouver, British Columbia, Canada, October 2005. http://www.aclweb.org/anthology/H/H05/H05-1091

3. Chan, Y.S., Roth, D.: Exploiting syntactico-semantic structures for relation extraction. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pp. 551–560. Association for Computational Linguistics, Portland, Oregon, USA, June 2011. http://www.aclweb.org/anthology/P11-1056

4. Doddington, G.R., Mitchell, A., Przybocki, M.A., Ramshaw, L.A., Strassel, S., Weischedel, R.M.: The automatic content extraction (ACE) program-tasks, data, and evaluation. In: LREC, vol. 2, p. 1 (2004)

5. Gupta, P., Schütze, H., Andrassy, B.: Table filling multi-task recurrent neural network for joint entity and relation extraction. In: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pp. 2537–2547 (2016)

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