Information Extraction Task

Information extraction (IE) focuses on automatically extracting structured information from unstructured text and other data sources, aiming to bridge the gap between human-readable content and machine-processable knowledge. Current research emphasizes developing unified IE frameworks capable of handling diverse tasks (e.g., named entity recognition, relation extraction) using large language models (LLMs) and retrieval-based approaches, often incorporating instruction tuning and in-context learning to improve generalization and efficiency. These advancements are crucial for building robust knowledge bases, powering applications like chatbots and question-answering systems, and improving efficiency in various domains such as biomedical research and business intelligence.