Gulmira, TolegenAlymzhan, ToleuZheng, Xiaoqing2017-01-112017-01-112016Gulmira, Tolegen., Alymzhan, Toleu., Zheng, Xiaoqing. (2016) Named Entity Recognition for Kazakh Using Conditional Random Fields / Извлечение именованных сущностей из текста на Казахском языке с использованием условных случайных полей. The 4-th International Conference on Computer Processing of Turkic Languages “TurkLang 2016”.http://turklang.kz/en/index.phphttp://nur.nu.edu.kz/handle/123456789/2234We addressed the Named Entity Recognition (NER) problem for the Kazakh language by using conditional random fields. Kazakh is a typical agglutinative language in which thousands of words could be generated by adding prefixes and suffixes to the same root, which arises a serious data sparsity problem for many NLP tasks. To reduce the data sparsity problem, a necessary preprocessing step is to split the words into their roots and morphemes by morphological analysis. In this study, we designed a CRF-based NER system for Kazakh, which leveraged the features derived from the results of a new-developed morphological analyzer, and found that the performance can be boosted by introducing such derived features. Moreover, we assembled a NER corpus which was manually annotated with location, organization and person names.enAttribution-NonCommercial-ShareAlike 3.0 United StatesKazakh languageagglutinative languagenamed entityNERCRFResearch Subject Categories::SOCIAL SCIENCES::Statistics, computer and systems science::Informatics, computer and systems scienceказахский языкагглютинативный языкименованные сущностиNERCRFArticle