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        <title>AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging</title>
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        <namePart type="given">Bill</namePart>
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    <abstract>We introduce an open-source web-based data annotation framework (AlpacaTag) for sequence tagging tasks such as named-entity recognition (NER). The distinctive advantages of AlpacaTag are three-fold. 1) Active intelligent recommendation: dynamically suggesting annotations and sampling the most informative unlabeled instances with a back-end active learned model; 2) Automatic crowd consolidation: enhancing real-time inter-annotator agreement by merging inconsistent labels from multiple annotators; 3) Real-time model deployment: users can deploy their models in downstream systems while new annotations are being made. AlpacaTag is a comprehensive solution for sequence labeling tasks, ranging from rapid tagging with recommendations powered by active learning and auto-consolidation of crowd annotations to real-time model deployment.</abstract>
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    <identifier type="doi">10.18653/v1/P19-3010</identifier>
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%0 Conference Proceedings
%T AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging
%A Lin, Bill Yuchen
%A Lee, Dong-Ho
%A Xu, Frank F.
%A Lan, Ouyu
%A Ren, Xiang
%Y Costa-jussà, Marta R.
%Y Alfonseca, Enrique
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F lin-etal-2019-alpacatag
%X We introduce an open-source web-based data annotation framework (AlpacaTag) for sequence tagging tasks such as named-entity recognition (NER). The distinctive advantages of AlpacaTag are three-fold. 1) Active intelligent recommendation: dynamically suggesting annotations and sampling the most informative unlabeled instances with a back-end active learned model; 2) Automatic crowd consolidation: enhancing real-time inter-annotator agreement by merging inconsistent labels from multiple annotators; 3) Real-time model deployment: users can deploy their models in downstream systems while new annotations are being made. AlpacaTag is a comprehensive solution for sequence labeling tasks, ranging from rapid tagging with recommendations powered by active learning and auto-consolidation of crowd annotations to real-time model deployment.
%R 10.18653/v1/P19-3010
%U https://aclanthology.org/P19-3010
%U https://doi.org/10.18653/v1/P19-3010
%P 58-63

Markdown (Informal)

[AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging](https://aclanthology.org/P19-3010) (Lin et al., ACL 2019)

• AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging (Lin et al., ACL 2019)

ACL

• Bill Yuchen Lin, Dong-Ho Lee, Frank F. Xu, Ouyu Lan, and Xiang Ren. 2019. AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 58–63, Florence, Italy. Association for Computational Linguistics.