Natural Language Processing

Publisher Summary This chapter deals with the topic of natural language processing in the field of artificial intelligence (AI). The subject of natural language processing covers processing issues at all levels of natural language understanding including speech recognition, syntactic and semantic analysis of sentences, reference to the discourse context, conversational inference and implicature, and discourse planning and generation. The chapter also covers the syntactic and semantic processing of sentences to deliver semantic objects suitable for referring, inferring, and other related functions. Even though this chapter is confined mainly to the syntactic and semantic section of the topic, it also demonstrates how it is impossible to entirely separate it from the broader context. All language processors can be viewed as being comprised of three elements. The first is grammar, which defines the legal ways in which constituents may combine both syntactically and semantically to yield other constituents. The second component of a processor is a non-deterministic algorithm that uses the rules of the grammar to deliver such structural descriptions for a given sentence. However, this component does not itself determine what happens when more than one rule can apply in a given state of the processor. This last responsibility devolves to the third component, the oracle, or mechanism for resolving such local processing ambiguities. The oracle decides which action should be taken at points in the analysis where the non-deterministic algorithm allows more than one. This chapter describes these three components in detail and briefly discusses the areas where these components are lacking.

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