---
dataset_info:
  features:
  - name: title
    dtype: string
  - name: did
    dtype: int64
  - name: data
    list:
    - name: img
      sequence: string
    - name: source_text
      dtype: string
    - name: title
      dtype: string
  - name: collection
    dtype: string
  - name: url
    dtype: string
  splits:
  - name: train
    num_bytes: 5698579
    num_examples: 1150
  download_size: 3328023
  dataset_size: 5698579
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---


# CQuAE base Documents Dataset Card

## Overview

The CQuAE dataset is a new French contextualized question-answering corpus focused on the education domain. It provides a structured annotation system that enhances the dataset's applicability for educational contexts and linguistic research. The primary documents used for annotations are detailed below, capturing a diversity of sources and content suitable for developing robust question-answering models.

## CQuAE Documents

The documents utilized in the CQuAE annotations are stored in a JSON file (`cquae-document.json`). Each document entry is represented as a dictionary, providing rich information about various textual sources. Below is the format and structure of how each document is stored:

- **`did` (int):** The document unique identifier. It serves as a reference for linking annotations to their respective sources.
- **`url` (str):** The source URL of the document. This provides access to the original location of the document for further reference or exploration.
- **`title` (str):** The title of the document. For Wikipedia entries, this represents the page title, whereas for educational content like "le livre scolaire," it represents the lesson name.
- **`data` (list):** A list of dictionaries, each corresponding to a specific paragraph or section within the document. The structure for each entry in the data list is as follows:
  - **`source_text` (str):** The actual textual content of the paragraph or section.
  - **`title` (str):** The title of the section, which is an empty string if the section does not possess a title.
  - **`img` (list):** Contains URLs of images associated with the section. An empty list indicates no images are present.

### Example Document Entry

```json
{
  "url": "https://www.lelivrescolaire.fr/page/6330739",
  "title": "L’organisme pluricellulaire, ensemble de cellules spécialisées",
  "data": [
    {
      "source_text": "On peut observer, à l’œil nu, un organisme pluricellulaire et les organes qui le constituent...",
      "title": "1 Les échelles du vivant [activité 1]",
      "img": []
    }
  ],
  "collection": "lls-svt-seconde",
  "did": 10
}
```

## Notes

- The dataset enhances educational resources for developing natural language understanding and question-answering systems.
- It provides context across a wide array of educational topics, allowing for diverse applications in computational linguistics and AI education tools.
- The dataset is versioned and maintained to address any linguistic inconsistencies or relevancy concerns identified in the initial release.

## Language

French

## License

Creative Commons Attribution-NonCommercial 4.0 International

## Citation

[CQuAE : Un nouveau corpus de question-réponse pour l’enseignement](https://aclanthology.org/2024.jeptalnrecital-taln.4/) (Gerald et al., JEP/TALN/RECITAL 2024)