metadata

license: unknown
task_categories:
  - text-generation
language:
  - en
tags:
  - question generation
pretty_name: LeaningQ-qg
size_categories:
  - 100K<n<1M
train-eval-index:
  - config: plain_text
    task: question-generation
    task_id: extractive_question_generation
    splits:
      train_split: train
      eval_split: validation
      test_split: test
    col_mapping:
      context: context
      questionsrc: question source
      question: question
    metrics:
      - type: squad
        name: SQuAD
dataset_info:
  features:
    - name: context
      dtype: string
    - name: questionsrc
      dtype: string
    - name: question
      dtype: string
  config_name: plain_text
  splits:
    - name: train
      num_examples: 188660
    - name: validation
      num_examples: 20630
    - name: test
      num_examples: 18227

Dataset Card for LearningQ-qg

Dataset Description

Repository: GitHub
Paper: LearningQ: A Large-scale Dataset for Educational Question Generation
Point of Contact: s.lamri@univ-bouira.dz

Dataset Summary

LearningQ, a challenging educational question generation dataset containing over 230K document-question pairs by [Guanliang Chen, Jie Yang, Claudia Hauff and Geert-Jan Houben]. It includes 7K instructor-designed questions assessing knowledge concepts being taught and 223K learner-generated questions seeking in-depth understanding of the taught concepts. This new version collected and corrected from over than 50000 error and more than 1500 type of error by Sidali Lamri

Use the dataset

from datasets import load_dataset
lq_dataset = load_dataset("sidovic/LearningQ-qg")
lq_dataset["train"][1]
len(lq_dataset["train"]),len(lq_dataset["validation"]),len(lq_dataset["test"])

Supported Tasks and Leaderboards

[Question generation]

Languages

[English]

Dataset Structure

Data Instances

An example of example looks as follows.

{
    
    "context": "This is a test context.",
    "questionsrc": "test context",
    "question": "Is this a test?"
}

Data Fields

The data fields are the same among all splits.

context: a string feature.
questionsrc: a string feature.
question: a string feature.

Data Splits

name	train	validation	test
LearningQ	188660	20630	18227

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

{
  author = {Sidali Lamri},
  title = {new LearningQ version for Question generation in transformers},
  year = {2023}
}
@paper{ICWSM18LearningQ,
    author = {Guanliang Chen, Jie Yang, Claudia Hauff and Geert-Jan Houben},
    title = {LearningQ: A Large-scale Dataset for Educational Question Generation},
    conference = {International AAAI Conference on Web and Social Media},
    year = {2018}
}

Contributions

[More Information Needed]