Word Sense Disambiguation (WSD) is a natural language processing task that involves determining which meaning of a word is being used in a given context. Many words have multiple meanings, and WSD aims to accurately identify the intended sense based on surrounding text. This process is crucial for improving the accuracy of various NLP applications, such as machine translation, information retrieval, and sentiment analysis. Techniques for WSD include supervised learning, unsupervised learning, and knowledge-based methods, making it a versatile tool in the field of AI. Effective WSD enhances the understanding of language and aids in better communication between humans and machines.
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AI Fundamentals