Reducing False Positives in the Construction of Adjective Scales
نویسنده
چکیده
Many adjectives that appear to be synonyms of one another differ in their intensity. Distinguishing the nuances between adjective synonyms is vital to linguistic understanding of a language, but WordNet currently does not encode the relative intensities of adjective synonyms that lie on the scale. Sheinman & Tokunaga (2009) proposed a solution of constructing Adjective Scales by data mining a web corpus. However, this process suffers from some limitations, most notably that of False Positives, which inaccurately suggest that adjective X is more or less intense than Y. This paper classifies the types of false positives that Sheinman’s method generates, then proposes a method to diminish the quantity of these false positives using linguistic searches in WordNet.
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