Lidor-Mashiach/mnli-training-paraphrase-augmentation
MNLI Training Paraphrase Augmentation Purpose This dataset contains new paraphrases created for training paraphrase augmentation during Phase B of the research project. It was not used as an NLI evaluation set. It was not used for paraphrase consistency evaluation. It is separate from the published MNLI Paraphrase Bank used for evaluation. The generation records report zero collisions with that evaluation bank. The CSV contains only the new augmentation rows. It… See the full description on the dataset page: https://huggingface.co/datasets/Lidor-Mashiach/mnli-training-paraphrase-augmentation.
MNLI Training Paraphrase Augmentation
Purpose
This dataset contains new paraphrases created for training paraphrase augmentation during Phase B of the research project.
It was not used as an NLI evaluation set.
It was not used for paraphrase consistency evaluation.
It is separate from the published MNLI Paraphrase Bank used for evaluation. The generation records report zero collisions with that evaluation bank.
The CSV contains only the new augmentation rows. It does not contain the full original MNLI training split. To create an augmented training set, combine these rows with the original MNLI training data.
Files
Columns
How the data was created
The augmentation rows were generated in three parallel parts and then merged into one CSV.
Candidate paraphrases were generated with humarin/chatgpt_paraphraser_on_T5_base.
Candidates were checked with MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli.
A candidate was kept only when it passed the following checks:
- Its length stayed within the allowed ratio relative to the original hypothesis.
- The candidate and original hypothesis were predicted to entail one another.
- The NLI relation between the premise and candidate matched the original gold label.
- The candidate was not a duplicate.
- The candidate did not appear in the published evaluation paraphrase bank.
The target was up to five new paraphrases per requested hypothesis.
Statistics
The merged rejection counts, duplicate checks, and experimental budgets appear in mnli-training-paraphrase-augmentation-stats.json.
Phase B context
The augmentation pool supported three experimental arms:
- targeted
- random
- oracle
The arm budgets were defined separately for BERT Base MNLI and DeBERTa Large MNLI.
These arm names describe the research design. They are not Hugging Face dataset splits.
Intended use
This dataset is intended for model training experiments that add new paraphrase rows to the original MNLI training data.
The original premise, hypothesis, and label are preserved. The new paraphrase is used as the augmented hypothesis.
Researchers should report which arm was used, the number of augmentation rows added, the model configuration, the random seed, and the exact repository version.
Not intended for evaluation
Do not treat this dataset as an independent MNLI validation or test set.
Do not use it as the paraphrase consistency benchmark published in the separate MNLI Paraphrase Bank repository.
Training and evaluation data should remain separated according to the experimental protocol.
Limitations
The paraphrases were generated and checked by models. They were not reviewed one by one by human annotators.
Automated checks can accept an imperfect paraphrase or reject a valid one.
The rows depend on the generator, verifier, filtering rules, and Phase B sampling design.
The CSV contains augmentation rows only. Users must obtain the original MNLI training data separately.
License
MultiNLI contains material from several sources. Its dataset card lists CC BY 3.0, CC BY-SA 3.0, MIT, and other source terms.
This repository uses the same mixed source terms notice.
Users must review the original MultiNLI documentation and follow the terms that apply to the relevant source material.
Associated research
This dataset was created during Phase B of the following research manuscript:
“Opening the Black Box: Localizing semantic inconsistency in NLI models with Deep k -Nearest Neighbors”
The manuscript is in preparation. It has not been submitted or published.
This section will be updated when a public preprint or accepted version becomes available.
Citation
Until the paper is public, please cite this dataset repository:
@misc{mashiach2026mnlitrainingparaphraseaugmentation,
author = {Lidor Mashiach},
title = {MNLI Training Paraphrase Augmentation},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/Lidor-Mashiach/mnli-training-paraphrase-augmentation}
}Please also cite the original MultiNLI paper.
Contact
Questions, corrections, and reproducibility reports can be posted in the Community tab of this repository.