Ambiguous Entity

Ambiguous entity resolution focuses on accurately identifying and linking mentions of entities (people, organizations, etc.) in text to their correct entries in a knowledge base, especially when the same name refers to multiple distinct entities. Current research emphasizes improving the performance of large language models (LLMs) and other machine learning models on this task, often employing techniques like improved tagging schemes, entity description fusion, and knowledge base reasoning to overcome challenges posed by ambiguous mentions and incomplete or noisy data. This work is crucial for improving the accuracy and reliability of information extraction and natural language processing systems across various applications, including financial crime detection and question answering.