Coref. Resolution & Relation Extraction

Coref. Resolution & Relation Extraction

This project aims to improve document-level coreference resolution, which involves identifying and linking mentions of the same entity throughout a text. Simultaneously, it tackles relation extraction, working to accurately identify and classify semantic relationships between entities in documents. By enhancing these interconnected capabilities, the research seeks to improve machines' ability to comprehend complex textual structures, supporting applications in document-level NLP tasks.

Director

  • Jinho Choi - Associate Professor at Emory University

Related Projects

Publications

  1. Towards Open-World Product Attribute Mining: A Lightly-Supervised Approach. Xu, L.; Zhang C.; Li, X.; Shang, J.; Choi, J. D. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2023.
  2. Online Coreference Resolution for Dialogue Processing: Improving Mention-Linking on Real-Time Conversations. Xu, L.; Choi, J. D. Proceedings of the Joint Conference on Lexical and Computational Semantics (*SEM), 2022.
  3. Modeling Explicit Task Interactions in Document-Level Joint Entity and Relation Extraction. Xu, L.; Choi, J. D. Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022.
  4. FantasyCoref: Coreference Resolution on Fantasy LiteratureThrough Omniscient Writer’s Point of View. Han, S.; Seo, S.; Kang, M.; Kim, J.; Choi, N.; Song, M.; and Choi, J. D. roceedings of the EMNLP Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC), 2021.
  5. Evaluation of Unsupervised Entity and Event Salience Estimation. Lu, J.; and Choi, J. D. Proceedings of the International Florida Artificial Intelligence Research Society Conference (FLAIRS), 2021.  
  6. Adapted End-to-End Coreference Resolution System for Anaphoric Identities in Dialogues. Xu, L.; and Choi, J. D. Proceedings of the EMNLP Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC): Shared Task on Anaphora Resolution in Dialogues, 2021.
  7. Revealing the Myth of Higher-Order Inference in Coreference Resolution. Xu, L.; and Choi, J. D. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020.