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    <abstract>Customized translation need pay spe-cial attention to the target domain ter-minology especially the named-entities for the domain. Adding linguistic features to neural machine translation (NMT) has been shown to benefit translation in many studies. In this paper, we further demonstrate that adding named-entity (NE) feature with named-entity recognition (NER) into the source language produces better translation with NMT. Our experiments show that by just including the different NE classes and boundary tags, we can increase the BLEU score by around 1 to 2 points using the standard test sets from WMT2017. We also show that adding NE tags using NER and applying in-domain adaptation can be combined to further improve customized machine translation.</abstract>
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%0 Conference Proceedings
%T Named-Entity Tagging and Domain adaptation for Better Customized Translation
%A Li, Zhongwei
%A Wang, Xuancong
%A Aw, Ai Ti
%A Chng, Eng Siong
%A Li, Haizhou
%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 li-etal-2018-named
%X Customized translation need pay spe-cial attention to the target domain ter-minology especially the named-entities for the domain. Adding linguistic features to neural machine translation (NMT) has been shown to benefit translation in many studies. In this paper, we further demonstrate that adding named-entity (NE) feature with named-entity recognition (NER) into the source language produces better translation with NMT. Our experiments show that by just including the different NE classes and boundary tags, we can increase the BLEU score by around 1 to 2 points using the standard test sets from WMT2017. We also show that adding NE tags using NER and applying in-domain adaptation can be combined to further improve customized machine translation.
%R 10.18653/v1/W18-2407
%U https://aclanthology.org/W18-2407
%U https://doi.org/10.18653/v1/W18-2407
%P 41-46

Markdown (Informal)

[Named-Entity Tagging and Domain adaptation for Better Customized Translation](https://aclanthology.org/W18-2407) (Li et al., NEWS 2018)

• Named-Entity Tagging and Domain adaptation for Better Customized Translation (Li et al., NEWS 2018)

ACL

• Zhongwei Li, Xuancong Wang, Ai Ti Aw, Eng Siong Chng, and Haizhou Li. 2018. Named-Entity Tagging and Domain adaptation for Better Customized Translation. In Proceedings of the Seventh Named Entities Workshop, pages 41–46, Melbourne, Australia. Association for Computational Linguistics.