README.md

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Dataset Card for "lince"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits Sample Size
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: http://ritual.uh.edu/lince
• Repository: More Information Needed
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 8.67 MB
• Size of the generated dataset: 53.81 MB
• Total amount of disk used: 62.48 MB

Dataset Summary

LinCE is a centralized Linguistic Code-switching Evaluation benchmark (https://ritual.uh.edu/lince/) that contains data for training and evaluating NLP systems on code-switching tasks.

Supported Tasks

More Information Needed

Languages

More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

lid_hineng

• Size of downloaded dataset files: 0.41 MB
• Size of the generated dataset: 2.28 MB
• Total amount of disk used: 2.69 MB

An example of 'validation' looks as follows.

{
    "idx": 0,
    "lid": ["other", "other", "lang1", "lang1", "lang1", "other", "lang1", "lang1", "lang1", "lang1", "lang1", "lang1", "lang1", "mixed", "lang1", "lang1", "other"],
    "words": ["@ZahirJ", "@BinyavangaW", "Loved", "the", "ending", "!", "I", "could", "have", "offered", "you", "some", "ironic", "chai-tea", "for", "it", ";)"]
}

lid_msaea

• Size of downloaded dataset files: 0.77 MB
• Size of the generated dataset: 4.66 MB
• Total amount of disk used: 5.43 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "idx": 0,
    "lid": ["ne", "lang2", "other", "lang2", "lang2", "other", "other", "lang2", "lang2", "lang2", "lang2", "lang2", "lang2", "lang2", "lang2", "lang2", "lang2", "lang2", "lang2", "lang2", "lang2", "other", "lang2", "lang2", "lang2", "ne", "lang2", "lang2"],
    "words": "[\"علاء\", \"بخير\", \"،\", \"معنوياته\", \"كويسة\", \".\", \"..\", \"اسخف\", \"حاجة\", \"بس\", \"ان\", \"كل\", \"واحد\", \"منهم\", \"بييقى\", \"مقفول\", \"عليه\"..."
}

lid_nepeng

• Size of downloaded dataset files: 0.52 MB
• Size of the generated dataset: 3.06 MB
• Total amount of disk used: 3.58 MB

An example of 'validation' looks as follows.

{
    "idx": 1,
    "lid": ["other", "lang2", "lang2", "lang2", "lang2", "lang1", "lang1", "lang1", "lang1", "lang1", "lang2", "lang2", "other", "mixed", "lang2", "lang2", "other", "other", "other", "other"],
    "words": ["@nirvikdada", "la", "hamlai", "bhetna", "paayeko", "will", "be", "your", "greatest", "gift", "ni", "dada", ";P", "#TreatChaiyo", "j", "hos", ";)", "@zappylily", "@AsthaGhm", "@ayacs_asis"]
}

lid_spaeng

• Size of downloaded dataset files: 1.13 MB
• Size of the generated dataset: 6.51 MB
• Total amount of disk used: 7.64 MB

An example of 'train' looks as follows.

{
    "idx": 0,
    "lid": ["other", "other", "lang1", "lang1", "lang1", "other", "lang1", "lang1"],
    "words": ["11:11", ".....", "make", "a", "wish", ".......", "night", "night"]
}

ner_hineng

• Size of downloaded dataset files: 0.13 MB
• Size of the generated dataset: 0.75 MB
• Total amount of disk used: 0.88 MB

An example of 'train' looks as follows.

{
    "idx": 1,
    "lid": ["en", "en", "en", "en", "en", "en", "hi", "hi", "hi", "hi", "hi", "hi", "hi", "en", "en", "en", "en", "rest"],
    "ner": ["O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-PERSON", "I-PERSON", "O", "O", "O", "B-PERSON", "I-PERSON"],
    "words": ["I", "liked", "a", "@YouTube", "video", "https://t.co/DmVqhZbdaI", "Kabhi", "Palkon", "Pe", "Aasoon", "Hai-", "Kishore", "Kumar", "-Vocal", "Cover", "By", "Stephen", "Qadir"]
}

Data Fields

The data fields are the same among all splits.

lid_hineng

• idx: a int32 feature.
• words: a list of string features.
• lid: a list of string features.

lid_msaea

• idx: a int32 feature.
• words: a list of string features.
• lid: a list of string features.

lid_nepeng

• idx: a int32 feature.
• words: a list of string features.
• lid: a list of string features.

lid_spaeng

• idx: a int32 feature.
• words: a list of string features.
• lid: a list of string features.

ner_hineng

• idx: a int32 feature.
• words: a list of string features.
• lid: a list of string features.
• ner: a list of string features.

Data Splits Sample Size

name	train	validation	test
lid_hineng	4823	744	1854
lid_msaea	8464	1116	1663
lid_nepeng	8451	1332	3228
lid_spaeng	21030	3332	8289
ner_hineng	1243	314	522

Dataset Creation

Curation Rationale

More Information Needed

Source Data

More Information Needed

Annotations

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

@inproceedings{aguilar-etal-2020-lince,
    title = "{L}in{CE}: A Centralized Benchmark for Linguistic Code-switching Evaluation",
    author = "Aguilar, Gustavo  and
      Kar, Sudipta  and
      Solorio, Thamar",
    booktitle = "Proceedings of The 12th Language Resources and Evaluation Conference",
    month = may,
    year = "2020",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://www.aclweb.org/anthology/2020.lrec-1.223",
    pages = "1803--1813",
    language = "English",
    ISBN = "979-10-95546-34-4",
}

Note that each LinCE dataset has its own citation too. Please see here for the correct citation on each dataset.

Contributions

Thanks to @lhoestq, @thomwolf, @gaguilar for adding this dataset.