Papers with document-level information extraction
MultiMUC: Multilingual Template Filling on MUC-4 (2024.eacl-long)
Copied to clipboard
William Gantt, Shabnam Behzad, Hannah An, Yunmo Chen, Aaron White, Benjamin Van Durme, Mahsa Yarmohammadi
| Challenge: | We present multilingual parallel template filling datasets for MUCs . systems were required to extract one template per incident, containing details about perpetrators, victims, weapons used . |
| Approach: | They introduce MultiMUC, the first multilingual parallel corpus for template filling . they obtain automatic translations from a strong multilingual machine translation system . |
| Outcome: | The proposed dataset includes translations of the classic MUC-4 template filling benchmark into Arabic, Chinese, Farsi, Korean, and Russian. |
Probing Representations for Document-level Event Extraction (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Document-level information extraction tasks require a more comprehensive understanding that often extends to the entire input document. |
| Approach: | They propose to use probing to analyze document-level information extraction representations by embedding probes into a standard dataset. |
| Outcome: | The proposed models improve argument detections but struggle with document length and cross-sentence discourse. |