Improved Named Entity Recognition using Machine Translation-based Cross-lingual Information
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Instituto Politécnico Nacional
2016
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| _version_ | 1876465417853075456 |
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| author | Sandipan Dandapat |
| author_facet | Sandipan Dandapat |
| contents | Improved Named Entity Recognition using Machine Translation-based Cross-lingual Information Sandipan Dandapat Andy Way Computación cross machine translation lingual information Named entity recognition In this paper, we describe a technique to improve named entity recognition in a resource-poor language (Hindi) by using cross-lingual information. We use an on-line machine translation system and a separate word alignment phase to find the projection of each Hindi word into the translated English sentence. We estimate the cross-lingual features using an English named entity recognizer and the alignment information. We use these cross-lingual features in a support vector machine-based classifier. The use of cross-lingual features improves F1 score by 2.1 points absolute (2.9% relative) over a good-performing baseline model. 2016 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61547469018 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.20 |
| format | Artículo científico |
| id | redalyc_61547469018 |
| institution | Redalyc |
| language | en |
| publishDate | 2016 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Improved Named Entity Recognition using Machine Translation-based Cross-lingual Information Sandipan Dandapat Computación cross machine translation lingual information Named entity recognition Improved Named Entity Recognition using Machine Translation-based Cross-lingual Information Sandipan Dandapat Andy Way Computación cross machine translation lingual information Named entity recognition In this paper, we describe a technique to improve named entity recognition in a resource-poor language (Hindi) by using cross-lingual information. We use an on-line machine translation system and a separate word alignment phase to find the projection of each Hindi word into the translated English sentence. We estimate the cross-lingual features using an English named entity recognizer and the alignment information. We use these cross-lingual features in a support vector machine-based classifier. The use of cross-lingual features improves F1 score by 2.1 points absolute (2.9% relative) over a good-performing baseline model. 2016 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61547469018 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.20 |
| title | Improved Named Entity Recognition using Machine Translation-based Cross-lingual Information |
| topic | Computación cross machine translation lingual information Named entity recognition |
| url | https://www.redalyc.org/articulo.oa?id=61547469018 |