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Evaluating open relation extraction over conversational texts
2014
In this thesis, for the first time the performance of Open IE systems on conversational data has been studied. Due to lack of test datasets in this domain, a method for creating the test dataset covering a wide range of conversational data has been proposed. Conversational text is more complex and challenging for relation extraction because of its cryptic content and ungrammatical colloquial language. As a consequence text simplification has been used as a remedy to empower Open IE tools for
doi:10.14288/1.0165856
fatcat:2nnw2lutkbastiymax56rr3qxi