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bhagvan kommadi
bhagvan kommadi

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History of NLP

** First Phase - Machine Translation Phase : 1940-1960**

  • The research on NLP started in early 1950s after Booth & Richens’ investigation and Weaver’s memorandum on machine translation in 1949.

  • 1954 was the year when a limited experiment on automatic translation from Russian to English demonstrated in the Georgetown-IBM experiment.

  • In the same year, the publication of the journal MT (Machine Translation) started.

  • The first international conference on Machine Translation (MT) was held in 1952 and second was held in 1956.

  • In 1961, the work presented in Teddington International Conference on Machine Translation of Languages and Applied Language analysis was the high point of this phase.

Second Phase - AI Influenced Phase – 1960-1970

  • In early 1961, the work began on the problems of addressing and constructing data or knowledge base. This work was influenced by AI.

  • In the same year, a BASEBALL question-answering system was also developed. The input to this system was restricted and the language processing involved was a simple one.

  • A much advanced system was described in Minsky (1968). This system, when compared to the BASEBALL question-answering system, was recognized and provided for the need of inference on the knowledge base in interpreting and responding to language input

Third Phase - Grammatico-logical Phase – 1970-1980

  • The grammatico-logical approach, towards the end of decade, helped us with powerful general-purpose sentence processors like SRI’s Core Language Engine and Discourse Representation Theory, which offered a means of tackling more extended discourse.

  • In this phase we got some practical resources & tools like parsers, e.g. Alvey Natural Language Tools along with more operational and commercial systems, e.g. for database query.

  • The work on lexicon in 1980s also pointed in the direction of grammatico-logical approach.

Fourth Phase - Lexical & Corpus Phase – 1990
There was a revolution in natural language processing in this decade with the introduction of machine learning algorithms for language processing.

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