Event Extraction: A Survey
It serves as a foundational resource for researchers and practitioners in NLP and related domains like newswire and biomedicine, but is incremental as a survey.
This survey tackles the problem of event extraction from text, a key NLP task involving detection, argument extraction, and role labeling, by providing a comprehensive overview including task definitions, evaluation methods, benchmark datasets, and a taxonomy of methodologies.
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.