Paper: A Quantitative Evaluation Of Linguistic Tests For The Automatic Prediction Of Semantic Markedness

ACL ID P95-1027
Title A Quantitative Evaluation Of Linguistic Tests For The Automatic Prediction Of Semantic Markedness
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1995
Authors

We present a corpus-based study of methods that have been proposed in the linguistics liter- ature for selecting the semantically unmarked term out of a pair of antonymous adjectives. Solutions to this problem are applicable to the more general task of selecting the positive term from the pair. Using automatically collected data, the accuracy and applicability of each method is quantified, and a statistical analysis of the significance of the results is performed. We show that some simple methods are indeed good indicators for the answer to the problem while other proposed methods fail to perform better than would be attributable to chance. In addition, one of the simplest methods, text frequency, dominates all others. We also ap- ply two generic statistical learning methods for combining ...