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        <title>A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition</title>
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    <name type="personal">
        <namePart type="given">Dingquan</namePart>
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        <namePart type="family">Peng</namePart>
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    <name type="personal">
        <namePart type="given">Kevin</namePart>
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            <title>Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)</title>
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    <abstract>We show how to adapt bilingual word embeddings (BWE‘s) to bootstrap a cross-lingual name-entity recognition (NER) system in a language with no labeled data. We assume a setting where we are given a comparable corpus with NER labels for the source language only; our goal is to build a NER model for the target language. The proposed multi-task model jointly trains bilingual word embeddings while optimizing a NER objective. This creates word embeddings that are both shared between languages and fine-tuned for the NER task.</abstract>
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%0 Conference Proceedings
%T A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition
%A Wang, Dingquan
%A Peng, Nanyun
%A Duh, Kevin
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F wang-etal-2017-multi
%X We show how to adapt bilingual word embeddings (BWE‘s) to bootstrap a cross-lingual name-entity recognition (NER) system in a language with no labeled data. We assume a setting where we are given a comparable corpus with NER labels for the source language only; our goal is to build a NER model for the target language. The proposed multi-task model jointly trains bilingual word embeddings while optimizing a NER objective. This creates word embeddings that are both shared between languages and fine-tuned for the NER task.
%U https://aclanthology.org/I17-2065/
%P 383-388

Markdown (Informal)

[A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition](https://aclanthology.org/I17-2065/) (Wang et al., IJCNLP 2017)

• A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition (Wang et al., IJCNLP 2017)

ACL

• Dingquan Wang, Nanyun Peng, and Kevin Duh. 2017. A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 383–388, Taipei, Taiwan. Asian Federation of Natural Language Processing.