This repository is a curated list of academic papers focused on the NLP task of Event Extraction. It serves as a valuable resource for researchers and practitioners looking to understand the landscape of event extraction techniques, from traditional pattern-matching approaches to modern deep learning models. The collection spans a wide range of methodologies, applications, and datasets within the field.

How It Works

The repository organizes papers by sub-task or methodology, including Pattern Matching, Machine Learning, Deep Learning, Semi-supervised Learning, Unsupervised Learning, Event Coreference, Surveys, Linguistics, Data, and Tools/Repos. This categorization allows users to quickly navigate and find relevant research on specific aspects of event extraction.

Quick Start & Requirements

• Installation: No installation is required as this is a curated list of papers.
• Requirements: Access to academic databases or search engines to retrieve the full papers.
• Resources: Links to papers, datasets, and tools are provided within the repository.

Highlighted Details

• Comprehensive coverage of event extraction research from 1993 to the present.
• Categorization by methodology (e.g., Deep Learning, Unsupervised Learning) and sub-task (e.g., Event Coreference).
• Inclusion of key datasets (MUC, ACE, etc.) and influential tools (FRED, TEES).
• Focus on both general and domain-specific applications (e.g., biomedical, financial, cybersecurity).

Maintenance & Community

• The repository is maintained by BaptisteBlouin.
• Community contributions are encouraged through GitHub.

Licensing & Compatibility

• The repository itself is likely under a permissive license (e.g., MIT), but the linked papers are subject to their respective academic publication licenses and copyright.

Limitations & Caveats

• This repository is a curated list and does not provide code or implementations for the papers. Users will need to find and access the papers independently.