Comprehensive Survey of Event Extraction Methods in Natural Language Processing

Event Extraction (Event Extraction) plays an essential role in NLP (Natural Language Processing) by automating the identification and extraction of events from unstructured textual data. This paper provides a comprehensive overview of event extraction, highlighting its significance in various domains such as security, law, and financial analysis. The paper categorizes event extraction into closed-domain and open-domain approaches. It also talks about various techniques like argument identification, event trigger identification, as well as event type classification. It explores methodologies including machine learning, pattern matching, & deep learning, emphasizing their application in different domains. Evaluation metrics to evaluate the effectiveness of EE systems are explored, including precision, recall, as well as the F1 score. Through a systematic review of the literature, the paper underscores the advancements, challenges, and future directions in EE, positioning it as a critical component in extracting actionable knowledge from textualsources.