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An Integrated Approach Using Conditional Random Fields for Named Entity Recognition and Person Property Extraction in Vietnamese Text

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5 Author(s)
Hoang-Quynh Le ; Coll. of Technol., KTLab, Vietnam Nat. Univ., Hanoi, Hanoi, Vietnam ; Mai-Vu Tran ; Nhat-Nam Bui ; Nguyen-Cuong Phan
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Personal names are among one of the most frequently searched items in web search engines and a person entity is always associated with numerous properties. In this paper, we propose an integrated model to recognize person entity and extract relevant values of a pre-defined set of properties related to this person simultaneously for Vietnamese. We also design a rich feature set by using various kind of knowledge resources and a apply famous machine learning method CRFs to improve the results. The obtained results show that our method is suitable for Vietnamese with the average result is 84 % of precision, 82.56% of recall and 83.39 % of F-measure. Moreover, performance time is pretty good, and the results also show the effectiveness of our feature set.

Published in:

Asian Language Processing (IALP), 2011 International Conference on

Date of Conference:

15-17 Nov. 2011