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TY - GEN N1 - NRC 50398 ID - cogprints6181 UR - http://cogprints.org/6181/ A1 - Turney, Peter D. Y1 - 2008/08// N2 - Recognizing analogies, synonyms, antonyms, and associations appear to be four distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks have been treated independently, using a wide variety of algorithms. These four semantic classes, however, are a tiny sample of the full range of semantic phenomena, and we cannot afford to create ad hoc algorithms for each semantic phenomenon; we need to seek a unified approach. We propose to subsume a broad range of phenomena under analogies. To limit the scope of this paper, we restrict our attention to the subsumption of synonyms, antonyms, and associations. We introduce a supervised corpus-based machine learning algorithm for classifying analogous word pairs, and we show that it can solve multiple-choice SAT analogy questions, TOEFL synonym questions, ESL synonym-antonym questions, and similar-associated-both questions from cognitive psychology. KW - analogies KW - synonyms KW - antonyms KW - associations KW - distributional hypothesis KW - semantics TI - A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations SP - 905 AV - public EP - 912 ER -