Natural Language Processing (NLP) is a crucial sub-field within artificial intelligence (AI), focusing on the interaction between computers and human (natural) languages. It makes use of algorithms and statistical models to empower computers to understand, interpret, and generate human language. NLP serves as an essential component in AI, with applications spanning a wide spectrum, including language translation, text classification, and chatbots.
In the realm of NLP, several notable challenges exist, such as syntactic ambiguity, semantic ambiguity, and contextual ambiguity. Syntactic ambiguity refers to the scenario where the same set of words can convey different meanings depending on the context and sentence structure. Semantic ambiguity implies that words can possess distinct meanings based on the context in which they are utilized. Contextual ambiguity, on the other hand, describes how the meaning of a word or phrase can fluctuate according to the specific context.