COREFERENCE RESOLUTION AND ENTITY DISAMBIGUATION FOR NATURAL LANGUAGE UNDERSTANDING

Resolution of coreferences and disambiguation of entities are two tasks that are crucial to natural language comprehension and are necessary for accurate text analysis and comprehension. This research study provides a comprehensive discussion of the difficulties, strategies, and practical implications associated with these responsibilities. In order to address the complexity of coreference resolution and entity disambiguation, we study a variety of methods, ranging from rule-based approaches to state-of-the-art machine learning models. This allows us to handle the complexities of both processes. In addition to this, we place an emphasis on the connection that exists between these tasks as well as the significance of each one in terms of the development of natural language processing systems.