apple/ml-mkqa
We introduce MKQA, an open-domain question answering evaluation set comprising 10k question-answer pairs aligned across 26 typologically diverse languages (260k question-answer pairs in total). The goal of this dataset is to provide a challenging benchmark for question answering quality across a wide set of languages. Please refer to our paper for details, MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering
This project provides a comprehensive collection of 260,000 question-answer pairs across 26 different languages. It's designed to help you evaluate how well your automated question-answering systems perform, especially when dealing with multiple languages. You input a question in any of the supported languages and expect an answer, which can be text, 'yes', 'no', or 'no answer.' This dataset is ideal for researchers and developers building multilingual information retrieval and conversational AI systems.
192 stars. No commits in the last 6 months.
Use this if you need a standardized benchmark to test the accuracy and linguistic diversity of your question-answering model across many languages.
Not ideal if you are looking for a dataset to train a question-answering model from scratch rather than evaluate an existing one.
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192
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Language
Python
License
Apache-2.0
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Last pushed
Jun 16, 2022
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