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Dataset Card for "lince"
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
Languages
Dataset Structure
Data Instances
lid_hineng
- Size of downloaded dataset files: 0.43 MB
- Size of the generated dataset: 2.39 MB
- Total amount of disk used: 2.82 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: 0.81 MB
- Size of the generated dataset: 4.89 MB
- Total amount of disk used: 5.69 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: 0.55 MB
- Size of the generated dataset: 3.21 MB
- Total amount of disk used: 3.75 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: 1.18 MB
- Size of the generated dataset: 6.83 MB
- Total amount of disk used: 8.01 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: 0.14 MB
- Size of the generated dataset: 0.79 MB
- Total amount of disk used: 0.92 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
: aint32
feature.words
: alist
ofstring
features.lid
: alist
ofstring
features.
lid_msaea
idx
: aint32
feature.words
: alist
ofstring
features.lid
: alist
ofstring
features.
lid_nepeng
idx
: aint32
feature.words
: alist
ofstring
features.lid
: alist
ofstring
features.
lid_spaeng
idx
: aint32
feature.words
: alist
ofstring
features.lid
: alist
ofstring
features.
ner_hineng
idx
: aint32
feature.words
: alist
ofstring
features.lid
: alist
ofstring
features.ner
: alist
ofstring
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
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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
@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.
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Models trained or fine-tuned on lince-benchmark/lince
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