README.md

metadata

paperswithcode_id: lince
pretty_name: Linguistic Code-switching Evaluation Dataset
dataset_info:
  - config_name: lid_spaeng
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: lid
        sequence: string
    splits:
      - name: test
        num_bytes: 1337727
        num_examples: 8289
      - name: train
        num_bytes: 4745003
        num_examples: 21030
      - name: validation
        num_bytes: 739950
        num_examples: 3332
    download_size: 1188861
    dataset_size: 6822680
  - config_name: lid_hineng
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: lid
        sequence: string
    splits:
      - name: test
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        num_examples: 1854
      - name: train
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        num_examples: 4823
      - name: validation
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        num_examples: 744
    download_size: 432854
    dataset_size: 2388064
  - config_name: lid_msaea
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: lid
        sequence: string
    splits:
      - name: test
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      - name: train
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        num_examples: 8464
      - name: validation
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        num_examples: 1116
    download_size: 803806
    dataset_size: 4885210
  - config_name: lid_nepeng
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: lid
        sequence: string
    splits:
      - name: test
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        num_examples: 3228
      - name: train
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        num_examples: 8451
      - name: validation
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        num_examples: 1332
    download_size: 545342
    dataset_size: 3211175
  - config_name: pos_spaeng
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: lid
        sequence: string
      - name: pos
        sequence: string
    splits:
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      - name: train
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      - name: validation
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        num_examples: 4298
    download_size: 819657
    dataset_size: 8067051
  - config_name: pos_hineng
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: lid
        sequence: string
      - name: pos
        sequence: string
    splits:
      - name: test
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        num_examples: 299
      - name: train
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        num_examples: 1030
      - name: validation
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        num_examples: 160
    download_size: 113872
    dataset_size: 749619
  - config_name: ner_spaeng
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: lid
        sequence: string
      - name: ner
        sequence: string
    splits:
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      - name: train
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        num_examples: 33611
      - name: validation
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        num_examples: 10085
    download_size: 3075520
    dataset_size: 19348258
  - config_name: ner_msaea
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: ner
        sequence: string
    splits:
      - name: test
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        num_examples: 1110
      - name: train
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        num_examples: 10103
      - name: validation
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        num_examples: 1122
    download_size: 938671
    dataset_size: 4686408
  - config_name: ner_hineng
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: lid
        sequence: string
      - name: ner
        sequence: string
    splits:
      - name: test
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        num_examples: 522
      - name: train
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        num_examples: 1243
      - name: validation
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        num_examples: 314
    download_size: 141285
    dataset_size: 781262
  - config_name: sa_spaeng
    features:
      - name: idx
        dtype: int32
      - name: words
        sequence: string
      - name: lid
        sequence: string
      - name: sa
        dtype: string
    splits:
      - name: test
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        num_examples: 4736
      - name: train
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        num_examples: 12194
      - name: validation
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        num_examples: 1859
    download_size: 1031412
    dataset_size: 5483882

Dataset Card for "lince"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• 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 and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

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

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

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

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.