Summary of the paper
| Title | Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers |
|---|---|
| Authors | Łukasz Degórski, Michał Marcińczuk and Adam Przepiórkowski |
| Abstract | 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. |
| Language | Single language |
| Topics | Information Extraction, Information Retrieval, Acquisition, Machine Learning, Other |
Full paper |
Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers |
Slides |
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| Bibtex | @InProceedings{DEGRSKI08.213, author = {Łukasz Degórski, Michał Marcińczuk and Adam Przepiórkowski}, title = {Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers}, booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)}, year = {2008}, month = {may}, date = {28-30}, address = {Marrakech, Morocco}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-4-0}, note = {http://www.lrec-conf.org/proceedings/lrec2008/}, language = {english} } |