There have been high hopes for Natural Language Processing. Natural Language Processing, also known
simply as NLP, is part of the broader field of Artificial Intelligence, the effort towards making machines think.
Computers may appear intelligent as they crunch numbers and process information with blazing speed. In truth,
computers are nothing but dumb slaves who only understand on or off and are limited to exact instructions. But
since the invention of the computer, scientists have been attempting to make computers not only appear intelligent
but be intelligent. A truly intelligent computer would not be limited to rigid computer language commands, but
instead be able to process and understand the English language. This is the concept behind Natural Language
The phases a message would go through during NLP would consist of message, syntax, semantics,
pragmatics, and intended meaning. (M. A. Fischer, 1987) Syntax is the grammatical structure. Semantics is the
literal meaning. Pragmatics is world knowledge, knowledge of the context, and a model of the sender. When
syntax, semantics, and pragmatics are applied, accurate Natural Language Processing will exist.
Alan Turing predicted of NLP in 1950 (Daniel Crevier, 1994, page 9):
'I believe that in about fifty years' time it will be possible to program computers .... to
make them play the imitation game so well that an average interrogator will not have more than
70 per cent chance of making the right identification after five minutes of questioning.'
But in 1950, the current computer technology was limited. Because of these limitations, NLP programs of
that day focused on exploiting the strengths the computers did have. For example, a program called SYNTHEX
tried to determine the meaning of sentences by looking up each word in its encyclopedia. Another early approach
was Noam Chomsky's at MIT. He believed that language could be analyzed without any reference to semantics or
pragmatics, just by simply looking at the syntax. Both of these techniques did not work. Scientists realized that
their Artificial Intelligence programs did not think like people do and since people are much more intelligent than
those programs they decided to make their programs think more closely like a person would. So in the late 1950s,
scientists shifted from trying to exploit the capabilities of computers to trying to emulate the human brain. (Daniel
Ross Quillian at Carnegie Mellon wanted to try to program the associative aspects of human memory to
create better NLP programs. (Daniel Crevier, 1994) Quillian's idea was to determine the meaning of a word by the
words around it. For example, look at these sentences:
After the strike, the president sent him away.
After the strike, the umpire sent him away.
Even though these sentences are the same except for one word, they have very different meaning because of the
meaning of the...