LsTam/CQuAE_documents

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

{
  "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 (Gerald et al., JEP/TALN/RECITAL 2024)