Datasets:
metadata
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: 8163175
num_examples: 42701
- name: validation
num_bytes: 190332
num_examples: 1000
- name: test
num_bytes: 190772
num_examples: 1000
download_size: 4322666
dataset_size: 8544279
- config_name: lv_en
features:
- name: id
dtype: int32
- name: source
dtype: string
- name: target
dtype: string
splits:
- name: train
num_bytes: 3644111
num_examples: 18749
- name: validation
num_bytes: 192511
num_examples: 1000
- name: test
num_bytes: 190867
num_examples: 1000
download_size: 1997959
dataset_size: 4027489
- config_name: no_en
features:
- name: id
dtype: int32
- name: source
dtype: string
- name: target
dtype: string
splits:
- name: train
num_bytes: 8761755
num_examples: 44322
- name: validation
num_bytes: 203815
num_examples: 1000
- name: test
num_bytes: 197127
num_examples: 1000
download_size: 4661188
dataset_size: 9162697
- config_name: zh_en
features:
- name: id
dtype: int32
- name: source
dtype: string
- name: target
dtype: string
splits:
- name: train
num_bytes: 9592148
num_examples: 50154
- name: validation
num_bytes: 192147
num_examples: 1000
- name: test
num_bytes: 195237
num_examples: 1000
download_size: 4733144
dataset_size: 9979532
configs:
- config_name: da_en
data_files:
- split: train
path: da_en/train-*
- split: validation
path: da_en/validation-*
- split: test
path: da_en/test-*
- config_name: lv_en
data_files:
- split: train
path: lv_en/train-*
- split: validation
path: lv_en/validation-*
- split: test
path: lv_en/test-*
- config_name: no_en
data_files:
- split: train
path: no_en/train-*
- split: validation
path: no_en/validation-*
- split: test
path: no_en/test-*
- config_name: zh_en
data_files:
- split: train
path: zh_en/train-*
- split: validation
path: zh_en/validation-*
- split: test
path: zh_en/test-*
Dataset Card for "code_x_glue_tt_text_to_text"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
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.