"Natural Language Processing" Artificial intelligence
Natural language processing (NLP) is the ability of a computer program to understand human language as it is spoken.
Language is meant for communicating about the world. By studying language, we can come to understand more about the world. We can test our theories about the world by how well they support our attempt to understand language. And, if we can succeed at building a computational model of language, we will have a powerful tool for communicating about the world. In this how we can exploit knowledge about the world, in combination with linguistic facts, to build computational natural language systems.
largest part of human linguistic communication occurs as speech. Written language is a fairly recent invention and still plays a less central role than speech in most activities. But processing written language (assuming it is written in unambiguous characters) is easier, in some ways, than processing speech. For example, to build a program that understands spoken language, we need all the facilities of a written language
understand as well as enough additional knowledge to handle all the noise and ambiguities of the audio signal.
Natural language processing includes both understanding and generation, as well as other tasks such as Multilingual translation.
Individual words are analyzed into their components, and nonword tokens, such as punctuation, are separated from the words.
Linear sequences of words are transformed into structures that show how the words relate to each other. Some word sequences may be rejected if they violate the language’s rules fo1 how words may be combined. For example, an English syntactic analyzer would reject the sentence “Boy the go the to store.”
The structures created by the syntactic analyzer are assigned meanings. In other words, a mapping is made between the syntactic structures and objects 1n the task domain. Structures for which no such mapping is possible may be rejected. For example, in most universes, the sentence “Colorless green ideas sleep furiously” (Chomsky, 1957] would be rejected as semantically anomalous.
The meaning of an individual sentence may depend on the sentences that precede it and may influence the meanings of the sentences that follow it. For example, the word “it” in the sentence, “J ohn wanted it,” depends on the prior discourse context, while the word “J ohn” may influence the meaning of later sentences (such as, “He always had.”)
The structure representing what was said is reinterpreted to determine what was actually meant. For example, the sentence “Do you know what time it is?” should be interpreted as a request to be told
Natural language processing includes both understanding and generation, as well as other tasks such as Multilingual translation.
Throughout this discussion of natural language processes the focus is on English. This happens to be convenient and turns Out to be where much of the work in the field has occurred. But the major issues we address are common to all natural languages, In fact, the techniques we discuss are particularly important in the task of translating from one natural language to another.
process down into the following pieces:
Morphological Analysis-
Individual words are analyzed into their components, and nonword tokens, such as punctuation, are separated from the words.
Syntactic Analysis-
Linear sequences of words are transformed into structures that show how the words relate to each other. Some word sequences may be rejected if they violate the language’s rules fo1 how words may be combined. For example, an English syntactic analyzer would reject the sentence “Boy the go the to store.”
Semantic Analysis-
The structures created by the syntactic analyzer are assigned meanings. In other words, a mapping is made between the syntactic structures and objects 1n the task domain. Structures for which no such mapping is possible may be rejected. For example, in most universes, the sentence “Colorless green ideas sleep furiously” (Chomsky, 1957] would be rejected as semantically anomalous.
Discourse Integration-
The meaning of an individual sentence may depend on the sentences that precede it and may influence the meanings of the sentences that follow it. For example, the word “it” in the sentence, “J ohn wanted it,” depends on the prior discourse context, while the word “J ohn” may influence the meaning of later sentences (such as, “He always had.”)
Pragmatic Analysis-
The structure representing what was said is reinterpreted to determine what was actually meant. For example, the sentence “Do you know what time it is?” should be interpreted as a request to be told
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