Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Sub-tasks:
multiple-choice-qa
Size:
10K - 100K
ArXiv:
License:
metadata
annotations_creators:
- derived
language:
- ara
- deu
- eng
- fra
- ita
- jpn
- kor
- nor
- por
- spa
- swe
license: cc-by-4.0
multilinguality: translated
source_datasets:
- zeta-alpha-ai/NanoNQ
- LiquidAI/nanobeir-multilingual-extended
task_categories:
- text-retrieval
task_ids:
- multiple-choice-qa
dataset_info:
- config_name: ar-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 4068842
num_examples: 5035
download_size: 2051862
dataset_size: 4068842
- config_name: ar-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: ar-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 4431
num_examples: 50
download_size: 4222
dataset_size: 4431
- config_name: de-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3091937
num_examples: 5035
download_size: 1937761
dataset_size: 3091937
- config_name: de-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: de-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3584
num_examples: 50
download_size: 4140
dataset_size: 3584
- config_name: en-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 2740852
num_examples: 5035
download_size: 1740902
dataset_size: 2740852
- config_name: en-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: en-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3132
num_examples: 50
download_size: 3644
dataset_size: 3132
- config_name: es-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3033561
num_examples: 5035
download_size: 1879179
dataset_size: 3033561
- config_name: es-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: es-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3590
num_examples: 50
download_size: 4089
dataset_size: 3590
- config_name: fr-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3151567
num_examples: 5035
download_size: 1932590
dataset_size: 3151567
- config_name: fr-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: fr-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3818
num_examples: 50
download_size: 4311
dataset_size: 3818
- config_name: it-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3005962
num_examples: 5035
download_size: 1880592
dataset_size: 3005962
- config_name: it-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: it-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3521
num_examples: 50
download_size: 4026
dataset_size: 3521
- config_name: ja-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3539146
num_examples: 5035
download_size: 2081014
dataset_size: 3539146
- config_name: ja-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: ja-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 6622
num_examples: 50
download_size: 5995
dataset_size: 6622
- config_name: ko-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3256050
num_examples: 5035
download_size: 2017503
dataset_size: 3256050
- config_name: ko-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: ko-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 4182
num_examples: 50
download_size: 4457
dataset_size: 4182
- config_name: no-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 2758468
num_examples: 5035
download_size: 1740408
dataset_size: 2758468
- config_name: no-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: no-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3218
num_examples: 50
download_size: 3791
dataset_size: 3218
- config_name: pt-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 2929253
num_examples: 5035
download_size: 1857783
dataset_size: 2929253
- config_name: pt-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: pt-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3435
num_examples: 50
download_size: 4050
dataset_size: 3435
- config_name: sv-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 2826385
num_examples: 5035
download_size: 1762668
dataset_size: 2826385
- config_name: sv-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 1796
num_examples: 57
download_size: 2473
dataset_size: 1796
- config_name: sv-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 3166
num_examples: 50
download_size: 3771
dataset_size: 3166
configs:
- config_name: ar-corpus
data_files:
- split: test
path: ar-corpus/test-*
- config_name: ar-qrels
data_files:
- split: test
path: ar-qrels/test-*
- config_name: ar-queries
data_files:
- split: test
path: ar-queries/test-*
- config_name: de-corpus
data_files:
- split: test
path: de-corpus/test-*
- config_name: de-qrels
data_files:
- split: test
path: de-qrels/test-*
- config_name: de-queries
data_files:
- split: test
path: de-queries/test-*
- config_name: en-corpus
data_files:
- split: test
path: en-corpus/test-*
- config_name: en-qrels
data_files:
- split: test
path: en-qrels/test-*
- config_name: en-queries
data_files:
- split: test
path: en-queries/test-*
- config_name: es-corpus
data_files:
- split: test
path: es-corpus/test-*
- config_name: es-qrels
data_files:
- split: test
path: es-qrels/test-*
- config_name: es-queries
data_files:
- split: test
path: es-queries/test-*
- config_name: fr-corpus
data_files:
- split: test
path: fr-corpus/test-*
- config_name: fr-qrels
data_files:
- split: test
path: fr-qrels/test-*
- config_name: fr-queries
data_files:
- split: test
path: fr-queries/test-*
- config_name: it-corpus
data_files:
- split: test
path: it-corpus/test-*
- config_name: it-qrels
data_files:
- split: test
path: it-qrels/test-*
- config_name: it-queries
data_files:
- split: test
path: it-queries/test-*
- config_name: ja-corpus
data_files:
- split: test
path: ja-corpus/test-*
- config_name: ja-qrels
data_files:
- split: test
path: ja-qrels/test-*
- config_name: ja-queries
data_files:
- split: test
path: ja-queries/test-*
- config_name: ko-corpus
data_files:
- split: test
path: ko-corpus/test-*
- config_name: ko-qrels
data_files:
- split: test
path: ko-qrels/test-*
- config_name: ko-queries
data_files:
- split: test
path: ko-queries/test-*
- config_name: no-corpus
data_files:
- split: test
path: no-corpus/test-*
- config_name: no-qrels
data_files:
- split: test
path: no-qrels/test-*
- config_name: no-queries
data_files:
- split: test
path: no-queries/test-*
- config_name: pt-corpus
data_files:
- split: test
path: pt-corpus/test-*
- config_name: pt-qrels
data_files:
- split: test
path: pt-qrels/test-*
- config_name: pt-queries
data_files:
- split: test
path: pt-queries/test-*
- config_name: sv-corpus
data_files:
- split: test
path: sv-corpus/test-*
- config_name: sv-qrels
data_files:
- split: test
path: sv-qrels/test-*
- config_name: sv-queries
data_files:
- split: test
path: sv-queries/test-*
tags:
- mteb
- text
NanoNQ is a smaller subset of a dataset which contains questions from real users, and it requires QA systems to read and comprehend an entire Wikipedia article that may or may not contain the answer to the question.
| Task category | Retrieval (text-to-text) |
| Domains | Academic, Web |
| Reference | Natural Questions: a Benchmark for Question Answering Research |
Source datasets:
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_task("MultilingualNanoNQRetrieval")
model = mteb.get_model(YOUR_MODEL)
mteb.evaluate(model, task)
To learn more about how to run models on mteb task check out the GitHub repository.
Citation
If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing as a part of the MMTEB Contribution.
@article{47761,
author = {Tom Kwiatkowski and Jennimaria Palomaki and Olivia Redfield and Michael Collins and Ankur Parikh and Chris Alberti and Danielle Epstein and Illia Polosukhin and Matthew Kelcey and Jacob Devlin and Kenton Lee and Kristina N. Toutanova and Llion Jones and Ming-Wei Chang and Andrew Dai and Jakob Uszkoreit and Quoc Le and Slav Petrov},
journal = {Transactions of the Association of Computational Linguistics},
title = {Natural Questions: a Benchmark for Question Answering Research},
year = {2019},
}
@article{enevoldsen2025mmtebmassivemultilingualtext,
title={MMTEB: Massive Multilingual Text Embedding Benchmark},
author={Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
publisher = {arXiv},
journal={arXiv preprint arXiv:2502.13595},
year={2025},
url={https://arxiv.org/abs/2502.13595},
doi = {10.48550/arXiv.2502.13595},
}
@article{muennighoff2022mteb,
author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Loïc and Reimers, Nils},
title = {MTEB: Massive Text Embedding Benchmark},
publisher = {arXiv},
journal={arXiv preprint arXiv:2210.07316},
year = {2022}
url = {https://arxiv.org/abs/2210.07316},
doi = {10.48550/ARXIV.2210.07316},
}
Dataset Statistics
Dataset Statistics
The following code contains the descriptive statistics from the task. These can also be obtained using:
import mteb
task = mteb.get_task("MultilingualNanoNQRetrieval")
desc_stats = task.metadata.descriptive_stats
{
"test": {
"num_samples": 55935,
"num_queries": 550,
"num_documents": 55385,
"number_of_characters": 27298486,
"documents_text_statistics": {
"total_text_length": 27272157,
"min_text_length": 1,
"average_text_length": 492.41052631578947,
"max_text_length": 46225,
"unique_texts": 54730
},
"documents_image_statistics": null,
"documents_audio_statistics": null,
"documents_video_statistics": null,
"queries_text_statistics": {
"total_text_length": 26329,
"min_text_length": 12,
"average_text_length": 47.87090909090909,
"max_text_length": 463,
"unique_texts": 550
},
"queries_image_statistics": null,
"queries_audio_statistics": null,
"queries_video_statistics": null,
"relevant_docs_statistics": {
"num_relevant_docs": 627,
"min_relevant_docs_per_query": 1,
"average_relevant_docs_per_query": 1.14,
"max_relevant_docs_per_query": 2,
"unique_relevant_docs": 627
},
"top_ranked_statistics": null
}
}
This dataset card was automatically generated using MTEB