Please use this identifier to cite or link to this item: http://dspace.ctu.edu.vn/jspui/handle/123456789/10783
Title: A feature-based model for nested named-entity recognition at VLSP-2018 ner evaluation campaign
Authors: Pham, Quang Nhat Minh
Keywords: Nested named-entity recognition
Feature-based model
Conditional random fields
Issue Date: 2018
Series/Report no.: Journal of Computer Science and Cybernetics;Vol.34(04) .- P.311–321
Abstract: In this paper, we describe our named-entity recognition system at VLSP 2018 evaluation campaign. We formalized the task as a sequence labeling problem using B-I-O encoding scheme and applied a feature-based model which combines word, word-shape features. Brown-cluster-based features, and word-embedding-based features. We compared several methods to deal with nested entities in the dataset. We showed that combining tags of entities at all levels to train a single sequence labeling model (joint-tag model) improved the accuracy of nested named-entity recognition.
URI: http://dspace.ctu.edu.vn/jspui/handle/123456789/10783
ISSN: 1813-9663
Appears in Collections:Tin học và Điều khiển học (Journal of Computer Science and Cybernetics)

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