Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
97 tokens/sec
GPT-4o
53 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Integrating knowledge bases to improve coreference and bridging resolution for the chemical domain (2404.10696v1)

Published 16 Apr 2024 in cs.CL

Abstract: Resolving coreference and bridging relations in chemical patents is important for better understanding the precise chemical process, where chemical domain knowledge is very critical. We proposed an approach incorporating external knowledge into a multi-task learning model for both coreference and bridging resolution in the chemical domain. The results show that integrating external knowledge can benefit both chemical coreference and bridging resolution.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (16)
  1. Scibert: A pretrained language model for scientific text. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 3615–3620.
  2. Liwei Cai and William Yang Wang. 2018. Kbgan: Adversarial learning for knowledge graph embeddings. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 1470–1480.
  3. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.
  4. A pipelined approach to anaphora resolution in chemical patents. In CLEF (Working Notes), pages 710–719.
  5. Chemu-ref: a corpus for modeling anaphora resolution in the chemical domain. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 1362–1375.
  6. Automated chemical reaction extraction from scientific literature. Journal of chemical information and modeling, 62(9):2035–2045.
  7. Oscar4: a flexible architecture for chemical text-mining. Journal of cheminformatics, 3(1):41.
  8. Spanbert: Improving pre-training by representing and predicting spans. Transactions of the Association for Computational Linguistics, 8:64–77.
  9. Chemdner: the drugs and chemical names extraction challenge. Journal of Cheminformatics, 7(1):0–11.
  10. Higher-order coreference resolution with coarse-to-fine inference. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 687–692.
  11. Extended overview of chemu 2021: Reaction reference resolution and anaphora resolution in chemical patents. CLEF (Working Notes), pages 693–709.
  12. Kojiro Machi and Masaharu Yoshioka. 2021. Hukb at chemu 2021 task 2: Anaphora resolution. In CLEF (Working Notes), pages 720–731.
  13. Adversarial learning of knowledge embeddings for the unified medical language system. AMIA Summits on Translational Science Proceedings, 2019:543.
  14. Scispacy: fast and robust models for biomedical natural language processing. arXiv preprint arXiv:1902.07669.
  15. Computational models of anaphora. Annual Review of Linguistics, 9:561–587.
  16. Multitask learning-based neural bridging reference resolution. In Proceedings of the 28th International Conference on Computational Linguistics. International Committee on Computational Linguistics.
User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (2)
  1. Pengcheng Lu (13 papers)
  2. Massimo Poesio (28 papers)

Summary

We haven't generated a summary for this paper yet.