Natural Language Processing is a range of computational techniques
for analyzing and representing naturally occurring texts at
one or more levels of linguistic analysis for the purpose of
achieving human-like language processing for a range of particular
tasks or applications. The levels of linguistic analysis are:
- Phonological: interpretation
of speech sounds within and across words
- Morphological: componential
analysis of words, including prefixes, suffixes and roots
- Lexical: word level
analysis including lexical meaning and part of speech analysis
- Syntactic: analysis
of words in a sentence in order to uncover the grammatical
structure of the sentence
- Semantic: determining
the possible meanings of a sentence, including disambiguation
of words in context
- Discourse: interpreting
structure and meaning conveyed by texts larger than a sentence
- Pragmatic: understanding
the purposeful use of language in situations, particularly
those aspects of language which require world knowledge
The above levels of linguistic processing reflect an increasing
size of unit of analysis as well as increasing complexity
and difficulty as we move from top to bottom. The larger the
unit of analysis becomes (i.e., from morpheme to word to sentence
to paragraph to full document), the less precise the language
phenomena and the greater the free choice and variability.
This decrease in precision results in fewer discernible rules
and more reliance on less predictable regularities as one
moves from the lowest to the highest levels. Additionally,
higher levels presume reliance on the lower levels of language
understanding, and the theories used to explain the data move
more into the areas of cognitive psychology and artificial
intelligence. As a result, the lower levels of language processing
have been more thoroughly investigated and incorporated into
NLP systems. The technologies developed at CNLP utilize all
these levels where appropriate, as well as relevant subsets
where appropriate.
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