History of natural language processing: Difference between revisions

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The [[Georgetown-IBM experiment|Georgetown experiment]] in 1954 involved fully automatic translation of more than sixty Russian sentences into English. The authors claimed that within three or five years, machine translation would be a solved problem.<ref>Hutchins, J. (2005)</ref> However, real progress was much slower, and after the [[ALPAC|ALPAC report]] in 1966, which found that ten years long research had failed to fulfill the expectations, funding for machine translation was dramatically reduced. Little further research in machine translation was conducted until the late 1980s, when the first [[statistical machine translation]] systems were developed.

Some notably successful NLP systems developed in the 1960s were [[SHRDLU]], a natural language system working in restricted "[[blocks world]]s" with restricted vocabularies, and [[ELIZA]], a simulation of a [[Rogerian psychotherapy|Rogerian psychotherapist]], written by [[Joseph Weizenbaum]] between 1964 to 1966. Using almost no information about human thought or emotion, ELIZA sometimes provided a startlingly human-like interaction. When the "patient" exceeded the very small knowledge base, ELIZA might provide a generic response, for example, responding to "My head hurts" with "Why do you say your head hurts?".

In 1969 [[Roger Schank]] introduced the [[conceptual dependency theory]] for natural language understanding.<ref>[[Roger Schank]], 1969, ''A conceptual dependency parser for natural language'' Proceedings of the 1969 conference on Computational linguistics, Sång-Säby, Sweden, pages 1-3</ref> This model, partially influenced by the work of [[Sydney Lamb]], was extensively used by Schank's students at [[Yale University]], such as Robert Wilensky, Wendy Lehnert, and [[Janet Kolodner]].