We study substitute vectors to solve the part-of-speech ambiguity problem in an unsupervised setting. Part-of-speech tagging is a crucial preliminary process in many natural language processing applications. Because many words in natural languages have more than one part-of-speech tag, resolving part-of-speech ambiguity is an important task. We claim that part-of-speech ambiguity can be solved using substitute vectors. A substitute vector is constructed with possible substitutes of a target word. This study is built on previous work which has proven that word substitutes are very fruitful for part-of-speech induction. Experiments show that our methodology works for words with high ambiguity.
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