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Natural language understanding
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Natural language understanding

Natural language understanding is a sub-field of artificial intelligence research devoted to making computers "understand" statements written in human languages.

Early systems such as SHRDLU, working in restricted "blocks worlds" with restricted vocabularies, worked extremely well, leading researchers to excessive optimism which was soon lost when the systems were extended to more realistic situations with real-world ambiguity and complexity.

Natural language understanding is sometimes referred to as an AI-complete problem, because natural language recognition seems to require extensive knowledge about the outside world and the ability to manipulate it. The definition of "understanding" is one of the major problems in natural language processing.

Some examples of the problems faced by natural language understanding systems:

The word "time" alone can be interpreted as three different parts of speech, (noun in the first example, verb in 2, 3, 4, and adjective in 5).
English is particularly bad in this regard because it has little inflectional morphology to distinguish between parts of speech.

To help this problem, some linguists and artificial intelligence researchers have proposed using an artificial language, that is capable of expressing all the nuance and subtlety of the natural languages we are familiar with, but would have mathematically inviolate grammar and spelling rules, to remove all possible confusion about what a sentence is trying to say, even if it were nonsense words. An example of such a constructed language that could be used for higher order human/computer communication is lojban.

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