Datasets:
annotations_creators:
- expert-generated
language:
- jam
language_creators:
- expert-generated
- found
license:
- other
multilinguality:
- monolingual
- other-english-based-creole
pretty_name: JamPatoisNLI
size_categories:
- n<1K
source_datasets:
- original
tags:
- creole
- low-resource-language
task_categories:
- text-classification
task_ids:
- natural-language-inference
Dataset Card for [Dataset Name]
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:
- jampatoisnli.github.io
- Repository:
- https://github.com/ruth-ann/jampatoisnli
- Paper:
- https://arxiv.org/abs/2212.03419
- Point of Contact:
- Ruth-Ann Armsrong: armstrongruthanna@gmail.com
Dataset Summary
JamPatoisNLI provides the first dataset for natural language inference in a creole language, Jamaican Patois. Many of the most-spoken low-resource languages are creoles. These languages commonly have a lexicon derived from a major world language and a distinctive grammar reflecting the languages of the original speakers and the process of language birth by creolization. This gives them a distinctive place in exploring the effectiveness of transfer from large monolingual or multilingual pretrained models.
Supported Tasks and Leaderboards
Natural language inference
Languages
Jamaican Patois
Data Fields
premise, hypothesis, label
Data Splits
Train: 250 Val: 200 Test: 200
Data set creation + Annotations
Premise collection: 97% of examples from Twitter; remaining pulled from literature and online cultural website
Hypothesis construction: For each premise, hypothesis written by native speaker (our first author) so that pair’s classification would be E, N or C
Label validation: Random sample of 100 sentence pairs double annotated by fluent speakers
Social Impact of Dataset
JamPatoisNLI is a low-resource language dataset in an English-based Creole spoken in the Caribbean, Jamaican Patois. The creation of the dataset contributes to expanding the scope of NLP research to under-explored languages across the world.
Dataset Curators
Citation Information
@misc{https://doi.org/10.48550/arxiv.2212.03419, doi = {10.48550/ARXIV.2212.03419},
url = {https://arxiv.org/abs/2212.03419},
author = {Armstrong, Ruth-Ann and Hewitt, John and Manning, Christopher},
keywords = {Computation and Language (cs.CL), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences, I.2.7},
title = {JamPatoisNLI: A Jamaican Patois Natural Language Inference Dataset},
publisher = {arXiv},
year = {2022},
copyright = {arXiv.org perpetual, non-exclusive license} }
Contributions
Thanks to Prof. Christopher Manning and John Hewitt for their contributions, guidance, facilitation and support related to the creation of this dataset.