Natural language processing

This is an old revision of this page, as edited by Derek Ross (talk | contribs) at 01:58, 18 March 2003 (Correct is not a good characterisation of answers in normal speech; helpful or unhelpful is better). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Natural language processing is a subfield of artificial intelligence. It studies the problems inherent in the processing and manipulation of natural language, but not, generally, natural language understanding. It should not be confused with computational linguistics, which is in the ___domain of linguistics.

The major tasks in NLP are:

Some problems which make NLP difficult:

Word boundary detection
In spoken language, there are no gaps between words; where to place the word boundary often depends on what choice makes the most sense grammatically and given the context.
Word sense disambiguation
Any given word can have several different meanings; we have to select the meaning which makes the most sense in context.
Syntactic ambiguity
The grammar for natural languages is not unambiguous, i.e. there are often multiple possible parse trees for a given sentence. Choosing the most appropriate one usually requires semantic and contextual information.
Speech acts and plans
Sentences often don't mean what they literally say; for instance a good answer to "Can you pass the salt" is to pass the salt; in most contexts "Yes" is not a good answer, although "No" is better and "I'm afraid that I can't see it" is better yet. Or again, if a class was not offered last year, "The class was not offered last year" is a better answer to the question "How many students failed the class last year?" than "None" is.