Datasets:
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---
annotations_creators:
- found
language_creators:
- found
language:
- da
- en
- lv
- nb
- zh
license:
- c-uda
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- translation
task_ids: []
pretty_name: CodeXGlueTtTextToText
tags:
- code-documentation-translation
dataset_info:
- config_name: da_en
features:
- name: id
dtype: int32
- name: source
dtype: string
- name: target
dtype: string
splits:
- name: train
num_bytes: 8163215
num_examples: 42701
- name: validation
num_bytes: 190340
num_examples: 1000
- name: test
num_bytes: 190780
num_examples: 1000
download_size: 8007867
dataset_size: 8544335
- config_name: lv_en
features:
- name: id
dtype: int32
- name: source
dtype: string
- name: target
dtype: string
splits:
- name: train
num_bytes: 3644127
num_examples: 18749
- name: validation
num_bytes: 192519
num_examples: 1000
- name: test
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num_examples: 1000
download_size: 3778501
dataset_size: 4027521
- config_name: no_en
features:
- name: id
dtype: int32
- name: source
dtype: string
- name: target
dtype: string
splits:
- name: train
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num_examples: 44322
- name: validation
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num_examples: 1000
- name: test
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num_examples: 1000
download_size: 8606833
dataset_size: 9162753
- config_name: zh_en
features:
- name: id
dtype: int32
- name: source
dtype: string
- name: target
dtype: string
splits:
- name: train
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num_examples: 50154
- name: validation
num_bytes: 192155
num_examples: 1000
- name: test
num_bytes: 195245
num_examples: 1000
download_size: 9353684
dataset_size: 9979596
---
# Dataset Card for "code_x_glue_tt_text_to_text"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits-sample-size)
- [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/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text
- **Paper:** https://arxiv.org/abs/2102.04664
### Dataset Summary
CodeXGLUE text-to-text dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text
The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/.
### Supported Tasks and Leaderboards
- `machine-translation`: The dataset can be used to train a model for translating Technical documentation between languages.
### Languages
da_en, lv_en, no_en, zh_en
## Dataset Structure
### Data Instances
#### da_en
An example of 'test' looks as follows.
```
{
"id": 0,
"source": "4 . K\u00f8r modellen , og udgiv den som en webtjeneste .\n",
"target": "4 . Run the model , and publish it as a web service .\n"
}
```
#### lv_en
An example of 'train' looks as follows.
```
{
"id": 0,
"source": "title : Pakalpojumu objektu izveide\n",
"target": "title : Create service objects\n"
}
```
#### no_en
An example of 'validation' looks as follows.
```
{
"id": 0,
"source": "2 . \u00c5pne servicevaren du vil definere komponenter fra en stykkliste for .\n",
"target": "2 . Open the service item for which you want to set up components from a BOM .\n"
}
```
#### zh_en
An example of 'validation' looks as follows.
```
{
"id": 0,
"source": "& # 124 ; MCDUserNotificationReadStateFilterAny & # 124 ; 0 & # 124 ; \u5305\u62ec \u901a\u77e5 , \u800c \u4e0d \u8003\u8651 \u8bfb\u53d6 \u72b6\u6001 \u3002 & # 124 ;\n",
"target": "| MCDUserNotificationReadStateFilterAny | 0 | Include notifications regardless of read state . |\n"
}
```
### Data Fields
In the following each data field in go is explained for each config. The data fields are the same among all splits.
#### da_en, lv_en, no_en, zh_en
|field name| type | description |
|----------|------|----------------------------------------|
|id |int32 | The index of the sample |
|source |string| The source language version of the text|
|target |string| The target language version of the text|
### Data Splits
|name |train|validation|test|
|-----|----:|---------:|---:|
|da_en|42701| 1000|1000|
|lv_en|18749| 1000|1000|
|no_en|44322| 1000|1000|
|zh_en|50154| 1000|1000|
## 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
https://github.com/microsoft, https://github.com/madlag
### Licensing Information
Computational Use of Data Agreement (C-UDA) License.
### Citation Information
```
@article{DBLP:journals/corr/abs-2102-04664,
author = {Shuai Lu and
Daya Guo and
Shuo Ren and
Junjie Huang and
Alexey Svyatkovskiy and
Ambrosio Blanco and
Colin B. Clement and
Dawn Drain and
Daxin Jiang and
Duyu Tang and
Ge Li and
Lidong Zhou and
Linjun Shou and
Long Zhou and
Michele Tufano and
Ming Gong and
Ming Zhou and
Nan Duan and
Neel Sundaresan and
Shao Kun Deng and
Shengyu Fu and
Shujie Liu},
title = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding
and Generation},
journal = {CoRR},
volume = {abs/2102.04664},
year = {2021}
}
```
### Contributions
Thanks to @madlag (and partly also @ncoop57) for adding this dataset. |