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---
license: cc
multilinguality: multilingual
task_categories:
- multiple-choice
pretty_name: Tokenization Robustness
tags:
- multilingual
- tokenization
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
  splits:
  - name: test
    num_bytes: 34461
    num_examples: 94
  download_size: 12077
  dataset_size: 34461
- 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
  splits:
  - name: test
    num_bytes: 8465
    num_examples: 28
  download_size: 9778
  dataset_size: 8465
- 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
  splits:
  - name: test
    num_bytes: 59495
    num_examples: 272
  download_size: 18551
  dataset_size: 59495
- 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
  splits:
  - name: test
    num_bytes: 30069
    num_examples: 101
  download_size: 15190
  dataset_size: 30069
- 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
  splits:
  - name: test
    num_bytes: 19569
    num_examples: 84
  download_size: 11491
  dataset_size: 19569
- config_name: named_entities
  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
  splits:
  - name: test
    num_bytes: 15490
    num_examples: 59
  download_size: 11633
  dataset_size: 15490
- config_name: orthographic_variations
  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
  splits:
  - name: test
    num_bytes: 6730
    num_examples: 30
  download_size: 7711
  dataset_size: 6730
- config_name: social_media_informal_text
  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
  splits:
  - name: test
    num_bytes: 23057
    num_examples: 107
  download_size: 13108
  dataset_size: 23057
- config_name: structural_text_elements
  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
  splits:
  - name: test
    num_bytes: 18802
    num_examples: 81
  download_size: 13081
  dataset_size: 18802
- config_name: temporal_expressions
  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
  splits:
  - name: test
    num_bytes: 5834
    num_examples: 27
  download_size: 8092
  dataset_size: 5834
configs:
- config_name: code_technical_content
  data_files:
  - split: test
    path: code_technical_content/test-*
- config_name: context-dependent_ambiguities
  data_files:
  - split: test
    path: context-dependent_ambiguities/test-*
- config_name: mathematical_scientific_notation
  data_files:
  - split: test
    path: mathematical_scientific_notation/test-*
- config_name: morphological_challenges
  data_files:
  - split: test
    path: morphological_challenges/test-*
- config_name: multi-linguality
  data_files:
  - split: test
    path: multi-linguality/test-*
- config_name: named_entities
  data_files:
  - split: test
    path: named_entities/test-*
- config_name: orthographic_variations
  data_files:
  - split: test
    path: orthographic_variations/test-*
- config_name: social_media_informal_text
  data_files:
  - split: test
    path: social_media_informal_text/test-*
- config_name: structural_text_elements
  data_files:
  - split: test
    path: structural_text_elements/test-*
- config_name: temporal_expressions
  data_files:
  - split: test
    path: temporal_expressions/test-*
---

# Dataset Card for Tokenization Robustness

<!-- Provide a quick summary of the dataset. -->

A comprehensive evaluation dataset for testing robustness of different tokenization strategies.

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

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]

<!-- Provide the basic links for the dataset. -->

- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

[More Information Needed]

### Out-of-Scope Use

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[More Information Needed]

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

The dataset contains multiple-choice questions with associated metadata about tokenization types and categories.

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

[More Information Needed]

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

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[More Information Needed]

#### Who are the source data producers?

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[More Information Needed]

### Annotations [optional]

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->

#### Annotation process

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[More Information Needed]

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

[More Information Needed]

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

The dataset focuses primarily on English text and may not generalize to other languages or tokenization schemes not covered in the evaluation.

### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

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**APA:**

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## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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