Argument Extraction

Argument extraction, a subfield of information extraction, aims to identify and extract arguments related to events from text, addressing challenges like implicit arguments and those spanning multiple sentences or documents. Current research focuses on leveraging large language models (LLMs) enhanced with techniques like heuristic prompting, chain-of-thought reasoning, and graph-based approaches to improve accuracy and handle complex document-level scenarios. These advancements are significant for various applications, including knowledge base population, question answering, and medical information retrieval, by enabling more accurate and comprehensive understanding of events from unstructured text.