Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers
نویسندگان
چکیده
The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a sequential combination of both. We show that applying ML methods with the support of a trivial grammar gives results better than a relatively complicated partial grammar, and much better than pure ML approach.
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