A Uniform Approach to Analogies, Synonyms, Antonyms, and AssociationsPeter D.TurneyauthorRecognizing 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.LanguageComputational LinguisticsSemanticsMachine LearningArtificial Intelligence2008-08Conference Paper