Datasets:

Multilinguality:
multilingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
ArXiv:
License:
albertvillanova's picture
Convert dataset to Parquet (#4)
ae1a41e verified
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 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": "&#124; MCDUserNotificationReadStateFilterAny &#124; 0 &#124; Include notifications regardless of read state . &#124;\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.