Word extraction from corpora and its part-of-speech estimation using distributional analysis
Shinsuke Mori, Makoto Nagao · 1996
Unknown words are inevitable at any step of analysis in natural language processing. We propose a method to extract words from a corpus and estimate the probability that each word belongs to given parts of speech (POSs), using a distributional analysis. Our experiments have shown that this method is effective for inferring the POS of unknown words.