ITM Web Conf.
Volume 12, 2017The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|Number of page(s)||5|
|Section||Session 1: Robotics|
|Published online||05 September 2017|
The Study of Graininess for Tibetan Named Entity Recognition
1 School of Information Engineering, Minzu University of China, Beijing, China
2 National Language Resource Monitoring & Research Center of Minority Languages, Beijing, China
Tibetan named entity recognition (NER), which is a fundamental part in Tibetan natural language processing, is the important subtask of Information extraction. In this paper, we surveyed the methods, effect and problems of Tibetan NER. And we discussed which kind of tokens that should be taken as the graininess for Tibetan NER task. The paper used two kinds of different graininess in a comparative experiment for Tibetan person names, location names and organization names, based on syllables, or based on words. From the result, we know that the person names based on syllable have better result than that based on words. Location names have small difference while species differ. But the organization names are more suitable based on words.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.