Datasets:
license: cc
multilinguality: multilingual
task_categories:
- multiple-choice
pretty_name: Tokenization Robustness
tags:
- multilingual
- tokenization
configs:
- config_name: code_technical_content
data_files:
- split: dev
path: code_technical_content/dev-*
- split: test
path: code_technical_content/test-*
- config_name: context-dependent_ambiguities
data_files:
- split: dev
path: context-dependent_ambiguities/dev-*
- split: test
path: context-dependent_ambiguities/test-*
- config_name: mathematical_scientific_notation
data_files:
- split: dev
path: mathematical_scientific_notation/dev-*
- split: test
path: mathematical_scientific_notation/test-*
- config_name: morphological_challenges
data_files:
- split: dev
path: morphological_challenges/dev-*
- split: test
path: morphological_challenges/test-*
dataset_info:
- config_name: code_technical_content
features:
- name: question
dtype: string
- name: choices
sequence: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: dev
num_bytes: 1424
num_examples: 4
- name: test
num_bytes: 34450
num_examples: 90
download_size: 20916
dataset_size: 35874
- config_name: context-dependent_ambiguities
features:
- name: question
dtype: string
- name: choices
sequence: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: dev
num_bytes: 2691
num_examples: 8
- name: test
num_bytes: 5998
num_examples: 20
download_size: 17480
dataset_size: 8689
- config_name: mathematical_scientific_notation
features:
- name: question
dtype: string
- name: choices
sequence: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: dev
num_bytes: 13033
num_examples: 58
- name: test
num_bytes: 48194
num_examples: 211
download_size: 29704
dataset_size: 61227
- config_name: morphological_challenges
features:
- name: question
dtype: string
- name: choices
sequence: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: dev
num_bytes: 13631
num_examples: 44
- name: test
num_bytes: 17256
num_examples: 57
download_size: 25621
dataset_size: 30887
Dataset Card for Tokenization Robustness
A comprehensive evaluation dataset for testing robustness of different tokenization strategies.
Dataset Details
Dataset Description
This dataset evaluates how robust language models are to different tokenization strategies and edge cases. It includes questions with multiple choice answers designed to test various aspects of tokenization handling.
- Curated by: R3
- Funded by [optional]: [More Information Needed]
- Shared by [optional]: [More Information Needed]
- Language(s) (NLP): [More Information Needed]
- License: cc
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- Demo [optional]: [More Information Needed]
Uses
Direct Use
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Out-of-Scope Use
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Dataset Structure
The dataset contains multiple-choice questions with associated metadata about tokenization types and categories.
Dataset Creation
Curation Rationale
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Source Data
Data Collection and Processing
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Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Bias, Risks, and Limitations
The dataset focuses primarily on English text and may not generalize to other languages or tokenization schemes not covered in the evaluation.
Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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