Event Argument Extraction

Event argument extraction (EAE) aims to identify and classify the key participants and circumstances surrounding events described in text, structuring unstructured information into a more readily usable format. Current research emphasizes improving the accuracy and efficiency of EAE, particularly at the document level, using techniques like large language models (LLMs) with prompting strategies, retrieval-augmented generation, and graph-based methods. These advancements are driven by a need for more robust and scalable solutions for applications such as knowledge base population, event prediction, and real-time information analysis across diverse domains and languages. The development of larger, more comprehensive datasets and standardized evaluation frameworks is also a significant focus to ensure fair comparison and facilitate progress in the field.