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metadata
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-*
  - config_name: multi-linguality
    data_files:
      - split: dev
        path: multi-linguality/dev-*
      - split: test
        path: multi-linguality/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
  - config_name: multi-linguality
    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: 5083
        num_examples: 23
      - name: test
        num_bytes: 15145
        num_examples: 61
    download_size: 20043
    dataset_size: 20228

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

Dataset Sources [optional]

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  • Paper [optional]: [More Information Needed]
  • 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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Who are the source data producers?

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Annotations [optional]

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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