Abstract:

 A part-of-speech disambiguation approach was given based on idiosyncratic rules in a parallel corpus unaligned at the lexical level. This approach focused on those words that occurred in the corpus at  very high frequency, while the part-of-speeches were difficult to determine. A number of idiosyncratic disambiguation rules were  constructed and an algorithm built on these rules was  applied on five typical words, among which were three Chinese words, “guoqu”, “jihua” and  “yu” and two English words, “back” and “so”. Experiments on a large scale parallel corpus obtained an F-score of 98.45% for the disambiguation of these words, and the results showed that the constructed rules would not be constrained by the length of context and the number of templates.

Key words: parallel corpus, part of speech disambiguation, words of POS ambiguity, automatic recognition, Chinese information processing