---
task_categories:
- question-answering
language:
- en
- fr
- de
- it
- es
- pt
pretty_name: mTRECQA
size_categories:
- 100K<n<1M
configs:
- config_name: default
  data_files:
  - split: train_en
    path: "eng-train.jsonl"
  - split: train_de
    path: "deu-train.jsonl"
  - split: train_fr
    path: "fra-train.jsonl"
  - split: train_it
    path: "ita-train.jsonl"
  - split: train_po
    path: "por-train.jsonl"
  - split: train_sp
    path: "spa-train.jsonl"
  - split: validation_en
    path: "eng-dev.jsonl"
  - split: validation_de
    path: "deu-dev.jsonl"
  - split: validation_fr
    path: "fra-dev.jsonl"
  - split: validation_it
    path: "ita-dev.jsonl"
  - split: validation_po
    path: "por-dev.jsonl"
  - split: validation_sp
    path: "spa-dev.jsonl"
  - split: test_en
    path: "eng-test.jsonl"
  - split: test_de
    path: "deu-test.jsonl"
  - split: test_fr
    path: "fra-test.jsonl"
  - split: test_it
    path: "ita-test.jsonl"
  - split: test_po
    path: "por-test.jsonl"
  - split: test_sp
    path: "spa-test.jsonl"
- config_name: en
  data_files:
  - split: train
    path: "eng-train.jsonl"
  - split: validation
    path: "eng-dev.jsonl"
  - split: test
    path: "eng-test.jsonl"
- config_name: de
  data_files:
  - split: train
    path: "deu-train.jsonl"
  - split: validation
    path: "deu-dev.jsonl"
  - split: test
    path: "deu-test.jsonl"
- config_name: fr
  data_files:
  - split: train
    path: "fra-train.jsonl"
  - split: validation
    path: "fra-dev.jsonl"
  - split: test
    path: "fra-test.jsonl"
- config_name: it
  data_files:
  - split: train
    path: "ita-train.jsonl"
  - split: validation
    path: "ita-dev.jsonl"
  - split: test
    path: "ita-test.jsonl"
- config_name: po
  data_files:
  - split: train
    path: "por-train.jsonl"
  - split: validation
    path: "por-dev.jsonl"
  - split: test
    path: "por-test.jsonl"
- config_name: sp
  data_files:
  - split: train
    path: "spa-train.jsonl"
  - split: validation
    path: "spa-dev.jsonl"
  - split: test
    path: "spa-test.jsonl"
---

## Dataset Description

**mTRECQA** originates from TREC-QA, which is created from the TREC 8 to TREC 13 QA tracks. TREC 8-12 constitutes the training set, while TREC 13 questions are set aside for development and testing.

The dataset has been translated into five European languages: French, German, Italian, Portuguese, and Spanish, as described in this paper: [Datasets for Multilingual Answer Sentence Selection](https://arxiv.org/abs/2406.10172 'Datasets for Multilingual Answer Sentence Selection').

## Splits:

For each language (English, French, German, Italian, Portuguese, and Spanish), we provide:

- **train** split
- **validation** split
- **test** split

### How to load them:
To use these splits, you can use the following snippet of code replacing ``[LANG]`` with a language identifier (en, fr, de, it, po, sp)

```
from datasets import load_dataset

# if you want the whole corpora
corpora = load_dataset("matteogabburo/mTRECQA")

"""
if you want the default splits of a specific language, replace [LANG] with an identifier in: en, fr, de, it, po, sp
dataset = load_dataset("matteogabburo/mTRECQA", "[LANG]")
"""
# example:
italian_dataset = load_dataset("matteogabburo/mTRECQA", "it")

```


## Format:
Each example has the following format:

```
{
  'eid': 42588,
  'qid': 1003,
  'cid': 4,
  'label': 1,
  'question': 'In welchem Land liegt die heilige Stadt Mekka?',
  'candidate': 'Der französische Präsident Jacques Chirac hat heute sein Beileid ausgedrückt, wegen des Todes von 250 Pilgern bei einem Brand, der am Dienstag in einem Lager in der Nähe der heiligen Stadt Mekka in Saudi-Arabien ausbrach.'
}
```

Where:

- **eid**: is the unique id of the example (question, candidate)
- **qid**: is the unique id of the question
- **cid**: is the unique id of the answer candidate
- **label**: identifies whether the answer candidate ``candidate`` is correct for the ``question`` (1 if correct, 0 otherwise)
- **question**: the question
- **candidate**: the answer candidate



## Citation

If you find this dataset useful, please cite the following paper:

**BibTeX:**
```
@misc{gabburo2024datasetsmultilingualanswersentence,
      title={Datasets for Multilingual Answer Sentence Selection}, 
      author={Matteo Gabburo and Stefano Campese and Federico Agostini and Alessandro Moschitti},
      year={2024},
      eprint={2406.10172},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2406.10172}, 
}
```