A dataset of the Chinese-Mongolian bilingual question-answer corpus in the legal field

<p indent="0mm">With the development of large model technology, intelligent question-answering system is more and more widely used in people’s work and life. However, due to the limited data resources, intelligent question answering systems of low-resource languages like Mongolian can not fully meet the application needs of users. Based on the existing Chinese question and answer (Q&amp;A) corpus, this study constructs 50,000 pairs of Chinese-Mongolian bilingual Q&amp;A corpus data with corresponding classification labels through the steps of rule screening, Chinese-Mongolian translation and manual correction. This dataset can provide researchers with rich and accurate question-answering samples for training and evaluating the performance of intelligent question-answering systems, as well as for tasks such as machine translation and text classification. The manual evaluation verifies that 92% of the corpus conforms to the Q&amp;A in the field of Chinese-Mongolian bilingual law. Therefore, the dataset holds significant value for advancing the research on the intelligent question-answering of various languages, including Chinese and Mongolia.

Authors

Publication Details

Journal
China Scientific Data
Published
2024-10-01
DOI
https://doi.org/10.11922/11-6035.csd.2024.0031
Citations
2
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.69
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article

A dataset of the Chinese-Mongolian bilingual question-answer corpus in the legal field

Siriguleng WANG, Audrey.Bonvin Unifr.Ch
2 citations
China Scientific Data
Natural Language Processing Techniques
0.69
article

A dataset of the Chinese-Mongolian bilingual question-answer corpus in the legal field

Siriguleng WANG, Audrey.Bonvin Unifr.Ch
article en
2 citations

Abstract

<p indent="0mm">With the development of large model technology, intelligent question-answering system is more and more widely used in people’s work and life. However, due to the limited data resources, intelligent question answering systems of low-resource languages like Mongolian can not fully meet the application needs of users. Based on the existing Chinese question and answer (Q&amp;A) corpus, this study constructs 50,000 pairs of Chinese-Mongolian bilingual Q&amp;A corpus data with corresponding classification labels through the steps of rule screening, Chinese-Mongolian translation and manual correction. This dataset can provide researchers with rich and accurate question-answering samples for training and evaluating the performance of intelligent question-answering systems, as well as for tasks such as machine translation and text classification. The manual evaluation verifies that 92% of the corpus conforms to the Q&amp;A in the field of Chinese-Mongolian bilingual law. Therefore, the dataset holds significant value for advancing the research on the intelligent question-answering of various languages, including Chinese and Mongolia.

China Scientific DataVol. 9(4)
Quality Education
Openalex Percentile: Top 22%
Natural Language Processing Techniques
0.69
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