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        <title>Universal Dependency Treebanks for Low-Resource Indian Languages: The Case of Bhojpuri</title>
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            <namePart type="given">Kalika</namePart>
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    <abstract>This paper presents the first dependency treebank for Bhojpuri, a resource-poor language that belongs to the Indo-Aryan language family. The objective behind the Bhojpuri Treebank (BHTB) project is to create a substantial, syntactically annotated treebank which not only acts as a valuable resource in building language technological tools, also helps in cross-lingual learning and typological research. Currently, the treebank consists of 4,881 annotated tokens in accordance with the annotation scheme of Universal Dependencies (UD). A Bhojpuri tagger and parser were created using machine learning approach. The accuracy of the model is 57.49% UAS, 45.50% LAS, 79.69% UPOS accuracy and 77.64% XPOS accuracy. The paper describes the details of the project including a discussion on linguistic analysis and annotation process of the Bhojpuri UD treebank.</abstract>
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%0 Conference Proceedings
%T Universal Dependency Treebanks for Low-Resource Indian Languages: The Case of Bhojpuri
%A Ojha, Atul Kr.
%A Zeman, Daniel
%Y Jha, Girish Nath
%Y Bali, Kalika
%Y L., Sobha
%Y Agrawal, S. S.
%Y Ojha, Atul Kr.
%S Proceedings of the WILDRE5– 5th Workshop on Indian Language Data: Resources and Evaluation
%D 2020
%8 May
%I European Language Resources Association (ELRA)
%C Marseille, France
%@ 979-10-95546-67-2
%G English
%F ojha-zeman-2020-universal
%X This paper presents the first dependency treebank for Bhojpuri, a resource-poor language that belongs to the Indo-Aryan language family. The objective behind the Bhojpuri Treebank (BHTB) project is to create a substantial, syntactically annotated treebank which not only acts as a valuable resource in building language technological tools, also helps in cross-lingual learning and typological research. Currently, the treebank consists of 4,881 annotated tokens in accordance with the annotation scheme of Universal Dependencies (UD). A Bhojpuri tagger and parser were created using machine learning approach. The accuracy of the model is 57.49% UAS, 45.50% LAS, 79.69% UPOS accuracy and 77.64% XPOS accuracy. The paper describes the details of the project including a discussion on linguistic analysis and annotation process of the Bhojpuri UD treebank.
%U https://aclanthology.org/2020.wildre-1.7
%P 33-38

Markdown (Informal)

[Universal Dependency Treebanks for Low-Resource Indian Languages: The Case of Bhojpuri](https://aclanthology.org/2020.wildre-1.7) (Ojha & Zeman, WILDRE 2020)

• Universal Dependency Treebanks for Low-Resource Indian Languages: The Case of Bhojpuri (Ojha & Zeman, WILDRE 2020)

ACL

• Atul Kr. Ojha and Daniel Zeman. 2020. Universal Dependency Treebanks for Low-Resource Indian Languages: The Case of Bhojpuri. In Proceedings of the WILDRE5– 5th Workshop on Indian Language Data: Resources and Evaluation, pages 33–38, Marseille, France. European Language Resources Association (ELRA).