# JamPatoisNLI: A Jamaican Patois Natural Language Inference Dataset

arXiv: https://arxiv.org/abs/2212.03419 · HTML: https://mlsanity.com/paper/2212.03419/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 56 references that are in the map.
- First posted on arXiv 7 Dec 2022.

## Builds on (most cited first, 30 of 30)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference](https://mlsanity.com/paper/1704.05426/) (2017)
- [A large annotated corpus for learning natural language inference](https://mlsanity.com/paper/1508.05326/) (2015)
- [BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models](https://mlsanity.com/paper/2106.10199/) (2021)
- [XNLI: Evaluating Cross-lingual Sentence Representations](https://mlsanity.com/paper/1809.05053/) (2018)
- [Annotation Artifacts in Natural Language Inference Data](https://mlsanity.com/paper/1803.02324/) (2018)
- [FastText.zip: Compressing text classification models](https://mlsanity.com/paper/1612.03651/) (2016)
- [XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning](https://mlsanity.com/paper/2005.00333/) (2020)
- [Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection](https://mlsanity.com/paper/2004.10643/) (2020)
- [Translation Artifacts in Cross-lingual Transfer Learning](https://mlsanity.com/paper/2004.04721/) (2020)
- [Low-resource Languages: A Review of Past Work and Future Challenges](https://mlsanity.com/paper/2006.07264/) (2020)
- [OCNLI: Original Chinese Natural Language Inference](https://mlsanity.com/paper/2010.05444/) (2020)
- [NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis](https://mlsanity.com/paper/2201.08277/) (2022)
- [Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for Bengali-English Machine Translation](https://mlsanity.com/paper/2009.09359/) (2020)
- [AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages](https://mlsanity.com/paper/2104.08726/) (2021)
- [Towards Ecologically Valid Research on Language User Interfaces](https://mlsanity.com/paper/2007.14435/) (2020)
- [ANLIzing the Adversarial Natural Language Inference Dataset](https://mlsanity.com/paper/2010.12729/) (2020)
- [A New Dataset for Natural Language Inference from Code-mixed Conversations](https://mlsanity.com/paper/2004.05051/) (2020)
- [What a Creole Wants, What a Creole Needs](https://mlsanity.com/paper/2206.00437/) (2022)
- [IndicXNLI: Evaluating Multilingual Inference for Indian Languages](https://mlsanity.com/paper/2204.08776/) (2022)
- [On Language Models for Creoles](https://mlsanity.com/paper/2109.06074/) (2021)
- [Universal Dependencies Parsing for Colloquial Singaporean English](https://mlsanity.com/paper/1705.06463/) (2017)
- [Ancestor-to-Creole Transfer is Not a Walk in the Park](https://mlsanity.com/paper/2206.04371/) (2022)
- [The first large scale collection of diverse Hausa language datasets](https://mlsanity.com/paper/2102.06991/) (2021)
- [MuCoT: Multilingual Contrastive Training for Question-Answering in Low-resource Languages](https://mlsanity.com/paper/2204.05814/) (2022)
- [An Augmented Translation Technique for low Resource language pair: Sanskrit to Hindi translation](https://mlsanity.com/paper/2006.08332/) (2020)
- [Data and Representation for Turkish Natural Language Inference](https://mlsanity.com/paper/2004.14963/) (2020)

## Built on by (most cited first, 11 of 11)

- [A Material Lens on Coloniality in NLP](https://mlsanity.com/paper/2311.08391/) (2023)
- ["It's how you do things that matters": Attending to Process to Better Serve Indigenous Communities with Language Technologies](https://mlsanity.com/paper/2402.02639/) (2024)
- [Krey`ol-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languages](https://mlsanity.com/paper/2405.05376/) (2024)
- [CreoleVal: Multilingual Multitask Benchmarks for Creoles](https://mlsanity.com/paper/2310.19567/) (2023)
- [Free Lunch: Robust Cross-Lingual Transfer via Model Checkpoint Averaging](https://mlsanity.com/paper/2305.16834/) (2023)
- [A Novel Cartography-Based Curriculum Learning Method Applied on RoNLI: The First Romanian Natural Language Inference Corpus](https://mlsanity.com/paper/2405.11877/) (2024)
- [mSTEB: Massively Multilingual Evaluation of LLMs on Speech and Text Tasks](https://mlsanity.com/paper/2506.08400/) (2025)
- [Language Evolution with Deep Learning](https://mlsanity.com/paper/2403.11958/) (2024)
- [Guylingo: The Republic of Guyana Creole Corpora](https://mlsanity.com/paper/2405.03832/) (2024)
- [Revealing Trends in Datasets from the 2022 ACL and EMNLP Conferences](https://mlsanity.com/paper/2404.08666/) (2024)
- [Limited-Resource Adapters Are Regularizers, Not Linguists](https://mlsanity.com/paper/2505.24525/) (2025)

## Abstract (arXiv)

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. While our work, along with previous work, shows that transfer from these models to low-resource languages that are unrelated to languages in their training set is not very effective, we would expect stronger results from transfer to creoles. Indeed, our experiments show considerably better results from few-shot learning of JamPatoisNLI than for such unrelated languages, and help us begin to understand how the unique relationship between creoles and their high-resource base languages affect cross-lingual transfer. JamPatoisNLI, which consists of naturally-occurring premises and expert-written hypotheses, is a step towards steering research into a traditionally underserved language and a useful benchmark for understanding cross-lingual NLP.