Abstract

The exact and automatic tagging the words in the texts of natural language is a very important problem. It will support a parsing for the texts, contribute to solve the polysemantic of the word, and help to access a semantic information, etc. Therefore, time tagging words in a text is always an essential problem, especially in th This paper will present the pruning techniques for tagging the texts of a natural language - the Viterbi algorithm [4]. The Viterbi pruning algorithm was tested with 1.000.000 words on the tag of the Wall Street Journal corpus [8].