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README.md
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---
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license: apache-2.0
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language:
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- ca
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- nl
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- fr
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- af
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- ga
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- gd
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- ms
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- oc
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---
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# Dataset Summary
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This is a variation of **mMARCO** by Bonifactio et al. used for the "Improving Low-Resource Retrieval Effectiveness using Zero-Shot Linguistic Similarity Transfer" paper
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**mMARCO** is a multilingual version of the [MS MARCO passage ranking dataset](https://microsoft.github.io/msmarco/).
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For more information, checkout our papers:
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* [**mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset**](https://arxiv.org/abs/2108.13897)
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* [**A cost-benefit analysis of cross-lingual transfer methods**](https://arxiv.org/abs/2105.06813)
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# Dataset Structure
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`queries/` contains both the translated dev queries used for evaluation under `/dev_small` and the translated train/judged queries used for training under `/train/`.
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The dev queries are in the following languages: Afrikaans, Catalan, Scottish Gaelic, Malay, Occitan, Sicilian, Cantonese.
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the train queries are in the following languages: Afrikaans, Catalan.
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`train_with_negs` contains the triples (query, positive doc, negative doc) used for training the models our ECIR 2025 IR4GOOD paper.
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# Licensing Information
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This dataset is released under [Apache license 2.0](https://www.apache.org/licenses/).
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# Citation Information
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If you use this dataset, please cite:
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```
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@article{DBLP:journals/corr/abs-2108-13897,
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author = {Luiz Bonifacio and
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Israel Campiotti and
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Roberto de Alencar Lotufo and
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Rodrigo Frassetto Nogueira},
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title = {mMARCO: {A} Multilingual Version of {MS} {MARCO} Passage Ranking Dataset},
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journal = {CoRR},
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volume = {abs/2108.13897},
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year = {2021},
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url = {https://arxiv.org/abs/2108.13897},
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eprinttype = {arXiv},
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eprint = {2108.13897},
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timestamp = {Mon, 20 Mar 2023 15:35:34 +0100},
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biburl = {https://dblp.org/rec/journals/corr/abs-2108-13897.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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```
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