Entity Disambiguation

This lecture covers the process of entity disambiguation, which involves linking text mentions in a document to entries in a knowledge base. It explores techniques such as Named Entity Recognition (NER) and the Viterbi algorithm for identifying and classifying entities. The lecture delves into the challenges of homonyms and synonyms in entity matching, and the use of Personalized PageRank for disambiguation. It also discusses the application of GPT models for entity matching, emphasizing the importance of prompt design and in-context learning. Evaluation results highlight the effectiveness of domain-specific prompts and simpler wording in improving entity matching accuracy.