EIGP: document-level event argument extraction with information enhancement generated based on prompts
Author:
Funder
Jilin Provincial Science and Technology Development Plan Project Fund
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10115-024-02213-4.pdf
Reference39 articles.
1. Lu Y, Lin H, Xu J, et al (2021) Text2Event: controllable sequence-to-structure generation for end-to-end event extraction. In: Zong C, Xia F, Li W, et al (eds) Proceedings of the 59th annual meeting of the association for computational linguistics and the 11th international joint conference on natural language processing (vol 1: Long Papers). Association for Computational Linguistics, Online, pp 2795–2806, https://doi.org/10.18653/v1/2021.acl-long.217, https://aclanthology.org/2021.acl-long.217
2. Li S, Ji H, Han J (2021) Document-level event argument extraction by conditional generation. In: Toutanova K, Rumshisky A, Zettlemoyer L, et al (eds) Proceedings of the 2021 conference of the North American chapter of the association for computational linguistics: human language technologies. Association for Computational Linguistics, Online, pp 894–908. https://doi.org/10.18653/v1/2021.naacl-main.69, https://aclanthology.org/2021.naacl-main.69
3. Hsu IH, Huang KH, Boschee E, et al (2022) DEGREE: a data-efficient generation-based event extraction model. In: Carpuat M, de Marneffe MC, Meza Ruiz IV (eds) Proceedings of the 2022 conference of the North American Chapter of the Association for computational linguistics: human language technologies. Association for Computational Linguistics, Seattle, United States, pp 1890–190. https://doi.org/10.18653/v1/2022.naacl-main.138, https://aclanthology.org/2022.naacl-main.138
4. Liu X, Huang H, Shi G, et al (2022) Dynamic prefix-tuning for generative template-based event extraction. In: Muresan S, Nakov P, Villavicencio A (eds) Proceedings of the 60th annual meeting of the association for computational linguistics (vol 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 5216–5228. https://doi.org/10.18653/v1/2022.acl-long.358, https://aclanthology.org/2022.acl-long.358
5. Hsu IH, Xie Z, Huang KH, et al (2023) AMPERE: AMR-aware prefix for generation-based event argument extraction model. In: Rogers A, Boyd-Graber J, Okazaki N (eds) Proceedings of the 61st annual meeting of the association for computational linguistics (vol 1: Long Papers). Association for Computational Linguistics, Toronto, Canada, pp 10976–10993. https://doi.org/10.18653/v1/2023.acl-long.615, https://aclanthology.org/2023.acl-long.615
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