Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers

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.

• Type: Conference
• Year: 2008
• Where: LREC
• Authors: Lukasz Degórski, Michal Marcinczuk, Adam Przepiórkowski
• Keywords: Education, LREC 2008, Partial Grammar, Partial Parsing, Pure Ml Approach