Entity Extraction

Entity extraction, the task of identifying and classifying named entities (e.g., people, organizations, locations) within text, aims to structure unstructured data for improved information retrieval and analysis. Current research heavily utilizes large language models (LLMs) and transformer architectures, often incorporating techniques like prompt engineering, multi-step planning, and multimodal integration to enhance accuracy and address challenges such as ambiguous mentions and data imbalance. This field is crucial for various applications, including knowledge graph construction, biomedical text mining, and financial crime detection, enabling more efficient and insightful analysis of large text corpora across diverse domains.