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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.
person named entity, property relation, property extraction, person property extraction, conditional random fields
Quang-Thuy Ha, Nhat-Nam Bui, Nguyen-Cuong Phan, Mai-Vu Tran, Hoang-Quynh Le, "An Integrated Approach Using Conditional Random Fields for Named Entity Recognition and Person Property Extraction in Vietnamese Text", Asian Language Processing, International Conference on, vol. 00, no. , pp. 115-118, 2011, doi:10.1109/IALP.2011.37
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