MLQA - Multilingual Question-Answering

Multilingual Question-Answering Dataset

By mlqa (From Huggingface) [source]

About this dataset

> > The dataset consists of several files in CSV format that provide context passages or paragraphs along with corresponding questions and answer options. The context passages serve as the source of information from which the questions are derived, and the answer options are potential answers to these questions. > > Each file in the dataset contains different language combinations for evaluation purposes. For example, mlqa.es.zh_test.csv focuses on testing multilingual question-answering models in Spanish and Chinese languages. Similarly, mlqa.hi.de_test.csv provides test data specifically for evaluating Hindi-German language pairs. > > In order to facilitate accurate evaluation of models' performance, each file includes multiple columns for context and answers. This allows researchers to assess how well their models can generate correct answers based on the given contexts. >

Research Ideas

> - Evaluation of multilingual question-answering models: This dataset can be used to evaluate the performance of different models designed for multilingual question-answering. By providing context, question, and answer pairs in multiple languages, it allows researchers to measure the accuracy and effectiveness of their models across different language pairs. > - Cross-lingual transfer learning: The MLQA dataset can be utilized to develop cross-lingual transfer learning techniques. Models trained on this dataset can learn to perform question-answering tasks in one language and then transfer that knowledge to answer questions in another language. > - Language understanding research: Researchers studying natural language processing (NLP) and language understanding can use this dataset to analyze how different languages handle questions and answers within various contexts. They can explore linguistic patterns, variations, and differences across languages by comparing the performance of NLP models trained on this dataset for both similar and dissimilar language pairs

Acknowledgements

> If you use this dataset in your research, please credit the original authors. > Data Source > >

License

> > > License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication > No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: mlqa.es.zh_test.csv

File: mlqa.hi.de_test.csv

File: mlqa.zh.de_test.csv

Acknowledgements

> If you use this dataset in your research, please credit the original authors. > If you use this dataset in your research, please credit mlqa (From Huggingface).