Papers with event extraction models
CrudeOilNews: An Annotated Crude Oil News Corpus for Event Extraction (2022.lrec-1)
Copied to clipboard
| Challenge: | a corpus of English crude oil news for event extraction is presented . the corpus contains 425 news articles with approximately 11k events annotated . |
| Approach: | They present a corpus of English Crude Oil news for event extraction . it is the first of its kind for Commodity News and contributes to text mining . |
| Outcome: | The proposed corpus of English crude oil news is the first of its kind for Commodity News . the annotated news articles are compared with the standard news articles . |
CMNEE:A Large-Scale Document-Level Event Extraction Dataset Based on Open-Source Chinese Military News (2024.lrec-main)
Copied to clipboard
| Challenge: | Current research focuses on the general news or financial domains, with relatively few studies for military domain. |
| Approach: | They propose to annotate Chinese military news events from documents using a schema for the military domain. |
| Outcome: | The proposed dataset is large-scale, document-level open-source for the military domain . it contains 17,000 documents and 29,223 events, which are all manually annotated . |
Learning from a Friend: Improving Event Extraction via Self-Training with Feedback from Abstract Meaning Representation (2023.findings-acl)
Copied to clipboard
| Challenge: | Existing data scarcity hinders the progress of event extraction, authors say . ACE-052 has 10 of the 33 event types with less than 80 annotations, authors claim . |
| Approach: | They propose a self-training with feedback framework that leverages large-scale unlabeled data to acquire feedback for each new event prediction from the unlabed data. |
| Outcome: | The proposed framework improves event extraction models even when unlabeled data are unavailable. |
Enhancing Document-level Event Argument Extraction with Contextual Clues and Role Relevance (2023.findings-acl)
Copied to clipboard
| Challenge: | Document-level event argument extraction is a challenging task for cross-sentence inference . previous work focused on document-level EAE, but recent work focused more on documentlevel . |
| Approach: | They propose a document-level event argument extraction model that captures contextual clues and latent role information. |
| Outcome: | The proposed model outperforms existing methods on two public datasets with 1.13 F1 and 2.64 F1 improvements on RAMS and WikiEvents respectively. |
Schema-based Data Augmentation for Event Extraction (2024.lrec-main)
Copied to clipboard
| Challenge: | Existing data augmentation methods rely on language models to train event extraction models. |
| Approach: | They propose a schema-based data augmentation method that utilizes event schemas to guide the data generation process. |
| Outcome: | The proposed method produces high-quality generated data and significantly improves model performance. |
LEMONADE: A Large Multilingual Expert-Annotated Abstractive Event Dataset for the Real World (2025.findings-acl)
Copied to clipboard
Sina Semnani, Pingyue Zhang, Wanyue Zhai, Haozhuo Li, Ryan Beauchamp, Trey Billing, Katayoun Kishi, Manling Li, Monica Lam
| Challenge: | Using a partially reannotated subset of the Armed Conflict Location & Event Data, we analyze 39,786 conflict events across 20 languages and 171 countries. |
| Approach: | They propose a large-scale conflict event dataset with extensive coverage of region-specific entities. |
| Outcome: | The proposed method detects event arguments and entities through holistic document understanding and normalizes them across the multilingual dataset. |