BagPack: A general framework to represent semantic relations

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We introduce a way to represent word pairs instantiating arbitrary semantic relations that keeps track of the contexts in which the words in the pair occur both together and independently. The resulting features are of sufficient generality to allow us, with the help of a standard supervised machine learning algorithm, to tackle a variety of unrelated semantic tasks with good results and almost no task-specific tailoring.
Long paper presented at GEMS - Geometric Models of Natural Language Semantics, workshop held in conjunction with the 12th Conference of the European Chapter of the Association for Computational Linguistics (EACL-09), Athens, Greece

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