Detecting and ordering adjectival scalemates
This addresses a specific NLP task for computational linguistics, with incremental improvements over existing methods.
The paper tackles the problem of automatically inferring and ordering adjectival scales (e.g., lukewarm, warm, hot) from a corpus, using a pattern-based method with filtering via similarity measures, and shows it performs at least as well as the current state-of-the-art.
This paper presents a pattern-based method that can be used to infer adjectival scales, such as <lukewarm, warm, hot>, from a corpus. Specifically, the proposed method uses lexical patterns to automatically identify and order pairs of scalemates, followed by a filtering phase in which unrelated pairs are discarded. For the filtering phase, several different similarity measures are implemented and compared. The model presented in this paper is evaluated using the current standard, along with a novel evaluation set, and shown to be at least as good as the current state-of-the-art.