Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
csv
Languages:
English
Size:
100K - 1M
Tags:
question generation
License:
File size: 3,700 Bytes
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---
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](https://github.com/AngusGLChen/LearningQ#readme)
- **Paper:** [LearningQ: A Large-scale Dataset for Educational Question Generation](https://ojs.aaai.org/index.php/ICWSM/article/view/14987/14837)
- **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](https://dz.linkedin.com/in/sidali-lamri)
### Use the dataset
```python
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] |