Datasets:
metadata
license: cc-by-nc-nd-4.0
task_categories:
- question-answering
tags:
- reasoning
- linguistics
- benchmark
pretty_name: L2
size_categories:
- 1K<n<10K
source_datasets:
- https://huggingface.co/datasets/ambean/lingOly
configs:
- config_name: default
data_files:
- split: test
path: test_small.zip
extra_gated_prompt: >-
### LingOly-TOO LICENSE AGREEMENT
This dataset is governed by a CC-BY-NC-ND-4.0 license.
In addition to this license, we ask that uses of the dataset are in line with
the Acceptable Use policy described below.
### Acceptable Use Policy
This dataset is intended as a benchmark for reasoning in large language
models. For the integrity of the benchmark, users should not:
* Re-distribute the questions or answers of the benchmark in formats (such as plain text) which leak the benchmark to web-scraping.
* Train language models directly using the content of this benchmark.
extra_gated_fields:
By clicking Submit below I accept the terms of the license and Acceptable Use policy: checkbox
extra_gated_button_content: Submit
Links
- Website
- Paper
- Leaderboard
- Repo
Summary
Dataset format
The data was created by generating up to 6 obfuscations per problem for 82 problems source from original LingOly benchmark.
{'question_n': # The question number in the problem
'prompt': # The main text of the question
'subprompts': [
{'questionpart_n': # For questions with several sub-parts (e.g. translating several sentences or matching paris of sentences)
'question': # The text of the question part
'answer': # The correct answer
'matches_human_scoring': # Annotation metadata
'fuzzy_matching': # Annotation metadata
'manual_edit': # Annotation metadata
}],
'metadata.preamble': # General text from the overall problem that is shared across all questions for that problem
'metadata.context': # Context text that includes important information, you should prepend your prompt with context for solvability
'metadata.obfuscated': # If this example was obfuscated or not
'metadata.obf_num': # Obfuscation counter (unique per problem). This is 0 if unobfuscated
'metadata.overall_question_n': # The problem number
'metadata.obfuscated_question_n': # Concatenation of problem number and obfuscation number
}
Citation
@article{khouja2025lingolytoo,
title={LINGOLY-TOO: Disentangling Memorisation from Reasoning with Linguistic Templatisation and Orthographic Obfuscation},
author={Khouja, Jude and Korgul, Karolina and Hellsten, Simeon and Yang, Lingyi and Neacșu, Vlad A. and Mayne, Harry and Kearns, Ryan O. and Bean, Andrew M. and Mahdi, Adam},
year={2025},
eprint=,
archivePrefix={arXiv},
primaryClass={cs.CL},
url=,
}