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| Title: | Learning Morphology with Morfette |
| Paper URL: | http://www.lrec-conf.org/proceedings/lrec2008/pdf/594_paper.pdf |
| Author: | Grzegorz Chrupała |
| Email: | click here to access email |
| Homepage: | http://www.lsv.uni-saarland.de/personalPages/gchrupala/index.html |
| Institution: | Saarland University |
| Author: | Georgiana Dinu |
| Email: | click here to access email |
| Institution: | Saarland University |
| Author: | Josef Van Genabith |
| Email: | click here to access email |
| Institution: | Dublin City University |
| Linguistic Field: | Computational Linguistics |
| Abstract: | Morfette is a modular, data-driven, probabilistic system which learns to perform joint morphological tagging and lemmatization from morphologically annotated corpora. The system is composed of two learning modules which are trained to predict morphological tags and lemmas using the Maximum Entropy classifier. The third module dynamically combines the predictions of the Maximum-Entropy models and outputs a probability distribution over tag-lemma pair sequences. The lemmatization module exploits the idea of recasting lemmatization as a classification task by using class labels which encode mappings from word forms to lemmas. Experimental evaluation results and error analysis on three morphologically rich languages show that the system achieves high accuracy with no language-specific feature engineering or additional resources. |
| Type: | Individual Paper |
| Status: | Completed |
| Venue: | LREC 2008 |
| URL: | http://www.lrec-conf.org/proceedings/lrec2008/pdf/594_paper.pdf |
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