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        <title>Connecting Distant Entities with Induction through Conditional Random Fields for Named Entity Recognition: Precursor-Induced CRF</title>
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        <namePart type="given">Wangjin</namePart>
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            <title>Proceedings of the Seventh Named Entities Workshop</title>
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            <namePart type="given">Nancy</namePart>
            <namePart type="family">Chen</namePart>
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        <name type="personal">
            <namePart type="given">Rafael</namePart>
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        <name type="personal">
            <namePart type="given">Xiangyu</namePart>
            <namePart type="family">Duan</namePart>
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        <name type="personal">
            <namePart type="given">Min</namePart>
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        <name type="personal">
            <namePart type="given">Haizhou</namePart>
            <namePart type="family">Li</namePart>
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    <abstract>This paper presents a method of designing specific high-order dependency factor on the linear chain conditional random fields (CRFs) for named entity recognition (NER). Named entities tend to be separated from each other by multiple outside tokens in a text, and thus the first-order CRF, as well as the second-order CRF, may innately lose transition information between distant named entities. The proposed design uses outside label in NER as a transmission medium of precedent entity information on the CRF. Then, empirical results apparently demonstrate that it is possible to exploit long-distance label dependency in the original first-order linear chain CRF structure upon NER while reducing computational loss rather than in the second-order CRF.</abstract>
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%0 Conference Proceedings
%T Connecting Distant Entities with Induction through Conditional Random Fields for Named Entity Recognition: Precursor-Induced CRF
%A Lee, Wangjin
%A Choi, Jinwook
%Y Chen, Nancy
%Y Banchs, Rafael E.
%Y Duan, Xiangyu
%Y Zhang, Min
%Y Li, Haizhou
%S Proceedings of the Seventh Named Entities Workshop
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F lee-choi-2018-connecting
%X This paper presents a method of designing specific high-order dependency factor on the linear chain conditional random fields (CRFs) for named entity recognition (NER). Named entities tend to be separated from each other by multiple outside tokens in a text, and thus the first-order CRF, as well as the second-order CRF, may innately lose transition information between distant named entities. The proposed design uses outside label in NER as a transmission medium of precedent entity information on the CRF. Then, empirical results apparently demonstrate that it is possible to exploit long-distance label dependency in the original first-order linear chain CRF structure upon NER while reducing computational loss rather than in the second-order CRF.
%R 10.18653/v1/W18-2402
%U https://aclanthology.org/W18-2402
%U https://doi.org/10.18653/v1/W18-2402
%P 9-13

Markdown (Informal)

[Connecting Distant Entities with Induction through Conditional Random Fields for Named Entity Recognition: Precursor-Induced CRF](https://aclanthology.org/W18-2402) (Lee & Choi, NEWS 2018)

• Connecting Distant Entities with Induction through Conditional Random Fields for Named Entity Recognition: Precursor-Induced CRF (Lee & Choi, NEWS 2018)

ACL

• Wangjin Lee and Jinwook Choi. 2018. Connecting Distant Entities with Induction through Conditional Random Fields for Named Entity Recognition: Precursor-Induced CRF. In Proceedings of the Seventh Named Entities Workshop, pages 9–13, Melbourne, Australia. Association for Computational Linguistics.