DEIE: Benchmarking Document-level Event Information Extraction with a Large-scale Chinese News Dataset
Yubing Ren, Yanan Cao, Hao Li, Yingjie Li, Zixuan ZM Ma, Fang Fang, Ping Guo, Wei Ma
Abstract
A text corpus centered on events is foundational to research concerning the detection, representation, reasoning, and harnessing of online events. The majority of current event-based datasets mainly target sentence-level tasks, thus to advance event-related research spanning from sentence to document level, this paper introduces DEIE, a unified large-scale document-level event information extraction dataset with over 56,000+ events and 242,000+ arguments. Three key features stand out: large-scale manual annotation (20,000 documents), comprehensive unified annotation (encompassing event trigger/argument, summary, and relation at once), and emergency events annotation (covering 19 emergency types). Notably, our experiments reveal that current event-related models struggle with DEIE, signaling a pressing need for more advanced event-related research in the future.- Anthology ID:
- 2024.lrec-main.410
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 4592–4604
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.410
- DOI:
- Cite (ACL):
- Yubing Ren, Yanan Cao, Hao Li, Yingjie Li, Zixuan ZM Ma, Fang Fang, Ping Guo, and Wei Ma. 2024. DEIE: Benchmarking Document-level Event Information Extraction with a Large-scale Chinese News Dataset. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 4592–4604, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- DEIE: Benchmarking Document-level Event Information Extraction with a Large-scale Chinese News Dataset (Ren et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2024.lrec-main.410.pdf