Summary of the paper
| Title | Improving NER in Arabic Using a Morphological Tagger |
|---|---|
| Authors | Benjamin Farber, Dayne Freitag, Nizar Habash and Owen Rambow |
| Abstract | We discuss a named entity recognition system for Arabic, and show how we incorporated the information provided by MADA, a full morphological tagger which uses a morphological analyzer. Surprisingly, the relevant features used are the capitalization of the English gloss chosen by the tagger, and the fact that an analysis is returned (that a word is not OOV to the morphological analyzer). The use of the tagger also improves over a third system which just uses a morphological analyzer, yielding a 14\% reduction in error over the baseline. We conduct a thorough error analysis to identify sources of success and failure among the variations, and show that by combining the systems in simple ways we can significantly influence the precision-recall trade-off. |
| Language | Single language |
| Topics | Named Entity recognition, Morphology, Lexicon, lexical database |
Full paper |
Improving NER in Arabic Using a Morphological Tagger |
Slides |
Improving NER in Arabic Using a Morphological Tagger |
| Bibtex | @InProceedings{FARBER08.625, author = {Benjamin Farber, Dayne Freitag, Nizar Habash and Owen Rambow}, title = {Improving NER in Arabic Using a Morphological Tagger}, 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} } |