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Dataset information
Dataset concatenating QA datasets with context available in French and open-source.
In addition, an augmented version of these datasets has been added (same context but different questions to create data in SQuAD 2.0 format).
In total, there are 221,348 training data, 910 validation data and 6,376 test data.
In practice, due to the restrictive license for the FQUAD 1.0 dataset, we can only share 200,617 rows of the 221,348 training data and 3,188 rows of the 6,376 test data.
So to obtain the complete dataset, the user will have to concatenate this dataset with the fquad dataset available here.
Our methodology is described in a blog post available in English or French.
Usage
from datasets import load_dataset
dataset = load_dataset("CATIE-AQ/frenchQA",sep=";")
dataset
DatasetDict({
train: Dataset({
features: ['context', 'question', 'answer', 'answer_start', 'dataset'],
num_rows: 200617
})
validation: Dataset({
features: ['context', 'question', 'answer', 'answer_start', 'dataset'],
num_rows: 910
})
test: Dataset({
features: ['id', 'title', 'context', 'question', 'answers'],
num_rows: 3188
})
})
Dataset
Dataset details
Dataset | Format | Train split | Dev split | Test split | Available in frenchQA |
---|---|---|---|---|---|
piaf | SQuAD 1.0 | 9 224 Q & A | X | X | Yes |
piaf_v2 | SQuAD 2.0 | 9 224 Q & A | X | X | Yes |
fquad | SQuAD 1.0 | 20 731 Q & A | 3 188 Q & A (is not used for training, but as a test dataset) | 2 189 Q & A (not freely available) | No due to the license |
fquad_v2 | SQuAD 2.0 | 20 731 Q & A | 3 188 Q & A (is not used for training, but as a test dataset) | X | Yes |
lincoln/newsquadfr | SQuAD 1.0 | 1 650 Q & A | 455 Q & A | X | Yes |
lincoln/newsquadfr_v2 | SQuAD 2.0 | 1 650 Q & A | 455 Q & A | X | Yes |
pragnakalp/squad_v2_french_translated | SQuAD 2.0 | 79 069 Q & A | X | X | Yes |
pragnakalp/squad_v2_french_translated_v2 | SQuAD 2.0 | 79 069 Q & A | X | X | Yes |
Columns
dataset_train = dataset['train'].to_pandas()
dataset_train.head()
context question answer answer_start dataset
0 Beyoncé Giselle Knowles-Carter (/ biːˈjɒnseɪ /... Quand Beyonce a-t-elle commencé à devenir popu... à la fin des années 1990 269 pragnakalp/squad_v2_french_translated
1 Beyoncé Giselle Knowles-Carter (/ biːˈjɒnseɪ /... Quand Beyonce a-t-elle quitté Destiny's Child ... 2003 549 pragnakalp/squad_v2_french_translated
2 Beyoncé Giselle Knowles-Carter (/ biːˈjɒnseɪ /... Qui a dirigé le groupe Destiny's Child ? Mathew Knowles 376 pragnakalp/squad_v2_french_translated
3 Beyoncé Giselle Knowles-Carter (/ biːˈjɒnseɪ /... Quand Beyoncé a-t-elle sorti Dangerously in Lo... 2003 549 pragnakalp/squad_v2_french_translated
4 Beyoncé Giselle Knowles-Carter (/ biːˈjɒnseɪ /... Combien de Grammy Awards Beyoncé a-t-elle gagn... cinq 629 pragnakalp/squad_v2_french_translated
- the
context
column contains the context - the
question
column contains the question - the
answer
column contains the answer (has been replaced byno_answer
for rows in SQuAD v2 format) - the
answer_start
column contains the start position of the answer in the context (has been replaced by-1
for rows in SQuAD v2 format) - the
dataset
column identifies the row's original dataset (if you wish to apply filters to it, rows in SQuAD v2 format are indicated with the suffix_v2
in the dataset name)
Split
train
corresponds to the concatenation of the training dataset frompragnakalp/squad_v2_english_translated
+lincoln/newsquadfr
+PIAFv1.2
+ the augmented version of each dataset in SQuADv2 format (no shuffle has been performed)validation
corresponds to the concatenation of the newsquadfr validation dataset + this same dataset expanded in SQuAD v2 format (= newsquadfr_v2) (no shuffle performed)test
corresponds to the concatenation of the fquad dataset SQuAD v1 in SQuAD v2 format (here we can only share the SQuAD v2 format)
Question type statistics
The question type distribution is as follows:
Type of question | Frequency in percent |
---|---|
What (que) | 55.02 |
Who (qui) | 15.96 |
How much (combien) | 7.92 |
When (quand) | 6.90 |
Where (où) | 3.15 |
How (comment) | 3.76 |
What (quoi) | 2.60 |
Why (pourquoi) | 1.25 |
Other | 3.44 |
The number of questions containing a negation, e.g. "What was the name of Chopin's first music teacher who was not an amateur musician?", is estimated at 3.55% of the total questions.
For information, the distribution of the complete dataset (containing FQUAD 1.0 and FQUAD 1.0 data in SQUAD 2.0 format) is as follows:
Type of question | Frequency in percent |
---|---|
What (que) | 55.12 |
Who (qui) | 16.24 |
How much (combien) | 7.56 |
When (quand) | 6.85 |
Where (où) | 3.98 |
How (comment) | 3.76 |
What (quoi) | 2.94 |
Why (pourquoi) | 1.41 |
Other | 2.14 |
The number of questions containing a negation, e.g. "What was the name of Chopin's first music teacher who was not an amateur musician?", is estimated at 3.07% of the total questions.
Citation
@misc {frenchQA2023,
author = { {ALBAR, Boris and BEDU, Pierre and BOURDOIS, Loïck} },
organization = { {Centre Aquitain des Technologies de l'Information et Electroniques} },
title = { frenchQA (Revision 6249cd5) },
year = 2023,
url = { https://huggingface.co/CATIE-AQ/frenchQA },
doi = { 10.57967/hf/0862 },
publisher = { Hugging Face }
}
License
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