task_categories:text2text-generation task_categories:text-classification task_ids:multi-class-classification task_ids:text-simplification annotations_creators:found language_creators:found multilinguality:monolingual size_categories:n<1K source_datasets:original language:en license:cc-by-sa-4.0 region:us
This dataset is a compilation of the OneStopEnglish corpus of texts written at three reading levels into one file.
Text documents are classified into three reading levels - ele, int, adv (Elementary, Intermediate and Advance).
This dataset demonstrates its usefulness for through two applica-tions - automatic  readability  assessment  and automatic text simplification.
The corpus consists of 189 texts, each in three versions/reading levels (567 in total).
@inproceedings{vajjala-lucic-2018-onestopenglish,
    title = {OneStopEnglish corpus: A new corpus for automatic readability assessment and text simplification},
    author = {Sowmya Vajjala and Ivana Lučić},
    booktitle = {Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications},
    year = {2018}
}
---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text2text-generation
- text-classification
task_ids:
- multi-class-classification
- text-simplification
paperswithcode_id: onestopenglish
pretty_name: OneStopEnglish corpus
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': ele
          '1': int
          '2': adv
  splits:
  - name: train
    num_bytes: 2278043
    num_examples: 567
  download_size: 1228804
  dataset_size: 2278043
---

# Dataset Card for OneStopEnglish corpus

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://github.com/nishkalavallabhi/OneStopEnglishCorpus
- **Repository:** https://github.com/purvimisal/OneStopCorpus-Compiled/raw/main/Texts-SeparatedByReadingLevel.zip
- **Paper:** https://www.aclweb.org/anthology/W18-0535.pdf
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary
OneStopEnglish is a corpus of texts written at three reading levels, and demonstrates its usefulness for through two applications - automatic readability assessment and automatic text simplification.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

An instance example:
```
{
  "text": "When you see the word Amazon, what’s the first thing you think...",
  "label": 0
}
```

Note that each instance contains the full text of the document.

### Data Fields

- `text`: Full document text. 
- `label`: Reading level of the document- ele/int/adv (Elementary/Intermediate/Advance).

### Data Splits

The OneStopEnglish dataset has a single _train_ split.

| Split | Number of instances |
|-------|--------------------:|
| train | 567                 |

## 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

Creative Commons Attribution-ShareAlike 4.0 International License

### Citation Information

[More Information Needed]

### Contributions

Thanks to [@purvimisal](https://github.com/purvimisal) for adding this dataset.