datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
boolq-natural-perturbationsBoolQ questions with semantic alteration and human verifications
@article{khashabi2020naturalperturbations,
title={Natural Perturbation for Robust Question Answering},
author={D. Khashabi and T. Khot and A. Sabhwaral},
journal={arXiv preprint},
year={2020}
}
AraDiCE-BoolQ
AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs
Overview
The AraDiCE dataset is designed to evaluate dialectal and cultural capabilities in large language models (LLMs). The dataset consists of post-edited versions of various benchmark datasets, curated for validation in cultural and dialectal contexts relevant to Arabic. In this repository, we present the BoolQ split of the data.
Evaluation
We have used lm-harness eval framework to for the… See the full description on the dataset page: https://huggingface.co/datasets/QCRI/AraDiCE-BoolQ.boolquesboolq_italian
BoolQ - Italian (IT)
This dataset is an Italian translation of BoolQ. BoolQ is a question-answering dataset composed of user queries issued to a search engine.
Dataset Details
The task is to predict whether the answer to the question is true or false based on the context provided in the question. A text snippet from Wikipedia is provided as the context for each question.
The dataset includes the following splits:
Train: 9,427 rows
Validation: 3,270 rows… See the full description on the dataset page: https://huggingface.co/datasets/sapienzanlp/boolq_italian.BoolQuestions
BoolQuestions: Does Dense Retrieval Understand Boolean Logic in Language?
Official repository for BoolQuestions: Does Dense Retrieval Understand Boolean Logic in Language?
GitHub Repository: https://github.com/zmzhang2000/boolean-dense-retrieval
HuggingFace Hub: https://huggingface.co/datasets/ustc-zhangzm/BoolQuestions
Paper: https://aclanthology.org/2024.findings-emnlp.156
BoolQuestions
BoolQuestions has been uploaded to Hugging Face Hub. You can download the… See the full description on the dataset page: https://huggingface.co/datasets/ustc-zhangzm/BoolQuestions.Indic-BoolQ
BoolQ Translated
Citation:
@inproceedings{clark2019boolq,
title = {BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions},
author = {Clark, Christopher and Lee, Kenton and Chang, Ming-Wei, and Kwiatkowski, Tom and Collins, Michael, and Toutanova, Kristina},
booktitle = {NAACL},
year = {2019},
}
Contributions:Thanks to @Srinidhi9113 and @Achala Nayak for adding the dataset.
boolq_skboolq-malay
Dataset Summary
This dataset comprises of both the original English and Malay translated version of Google's BoolQ which
is a question/answering dataset for yes (1)/no (0) questions.
For our use case, we've edited this dataset to comprise passage-question pairs and a answer column that determines whether a the question's answer is yes (1) or no (0).
Malay Version Generation
The Malay section of the dataset was done by translating the above dataset using OpenAI's… See the full description on the dataset page: https://huggingface.co/datasets/wanadzhar913/boolq-malay.boolq_3Labelboolq-mk
BoolQ MK version
This dataset is a Macedonian adaptation of the BoolQ dataset, originally curated (English -> Serbian) by Aleksa Gordić. It was translated from Serbian to Macedonian using the Google Translate API.
You can find this dataset as part of the macedonian-llm-eval GitHub and HuggingFace.
The dataset can be used to evaluate the models described in the paper Towards Open Foundation Language Model and Corpus for Macedonian: A Low-Resource Language.
Why Translate from… See the full description on the dataset page: https://huggingface.co/datasets/LVSTCK/boolq-mk.shuffle_boolqNO-BoolQ
Dataset Card for NO-BoolQ
NO-BoolQ is machine translated from Google Boolq dataset. It is a question answering dataset split with train, test and validation set the same with it's original dataset.
This dataset belongs to NLEBench Norwegian benchmarks for evaluation on Norwegian Natrual Language Undersanding (NLU) tasks.
Licensing Information
This dataset is built upon the existing datasets. We therefore follow its original license information.
Citation… See the full description on the dataset page: https://huggingface.co/datasets/NorGLM/NO-BoolQ.boolq_sharegptboolq_italian
BoolQ - Italian (IT)
This dataset is an Italian translation of BoolQ. BoolQ is a question-answering dataset composed of user queries issued to a search engine.
Dataset Details
The task is to predict whether the answer to the question is true or false based on the context provided in the question. A text snippet from Wikipedia is provided as the context for each question.
The dataset includes the following splits:
Train: 9,285 rows
Validation: 3,236 rows… See the full description on the dataset page: https://huggingface.co/datasets/s-conia/boolq_italian.boolq-malay-with-chain-of-thought
Dataset Summary
This dataset comprises of both the original English and Malay translated version of Google's BoolQ which
is a question/answering dataset for yes (1)/no (0) questions.
For our use case, we've edited this dataset to comprise passage-question pairs and a answer column that determines whether a the question's answer is yes (1) or no (0).
Additionally, this dataset also has a Chain-of-Thought/reasoning column which details a step-by-step reasoning for the answer.… See the full description on the dataset page: https://huggingface.co/datasets/wanadzhar913/boolq-malay-with-chain-of-thought.boolq-3k-jagoogle-boolq-sharegpt
Dataset Summary
BoolQ is a question answering dataset created by Google for yes/no questions containing 15942 examples. These questions are naturally
occurring ---they are generated in unprompted and unconstrained settings.
Each example was a triplet of (question, passage, answer), with the title of the page as optional additional context. I converted it to ShareGPT where the passage and answer are combined into one cohesive response from the AI.
I plan to use this as regularization… See the full description on the dataset page: https://huggingface.co/datasets/Kquant03/google-boolq-sharegpt.vjkhambe-boolq-eval