Event Extraction: A Survey

TL;DR

This survey comprehensively reviews event extraction in NLP, covering tasks, evaluation methods, datasets, methodologies, and future directions across diverse domains.

Contribution

It provides a detailed taxonomy of event extraction methods, summarizes benchmark datasets, and outlines future research challenges in the field.

Findings

Summarizes key datasets and evaluation metrics

Classifies methodologies into distinct categories

Identifies open challenges and future directions

Abstract

Extracting the reported events from text is one of the key research themes in natural language processing. This process includes several tasks such as event detection, argument extraction, role labeling. As one of the most important topics in natural language processing and natural language understanding, the applications of event extraction spans across a wide range of domains such as newswire, biomedical domain, history and humanity, and cyber security. This report presents a comprehensive survey for event detection from textual documents. In this report, we provide the task definition, the evaluation method, as well as the benchmark datasets and a taxonomy of methodologies for event extraction. We also present our vision of future research direction in event detection.