Deducing Linguistic Structure from the Statistics of Large Corpora.

摘要

Within the last two years, approaches using both stochastic and symbolic techniques have proved adequate to deduce lexical ambiguity resolution rules with less than 3-4% error rate, when trained on moderate sized (500K word) corpora of English text (e.g. Church, 1988; Hindle, 1989). The success of these techniques suggests that much of the grammatical structure of language may be derived automatically through distributional analysis, an approach attempted and abandoned in the 1950s. We describe here two experiments to see how far purely distributional techniques can be pushed to automatically provide both a set of part of speech tags for English, and a grammatical analysis of free English text. We also discuss the state of a tagged NL corpus to aid such research (now amounting to 4 million words of hand-corrected part-of-speech tagging).