---
license: cc
multilinguality: multilingual
task_categories:
- multiple-choice
pretty_name: Tokenization Robustness
tags:
- multilingual
- tokenization
configs:
- config_name: social_media_informal_text
  data_files:
  - split: tokenizer_robustness_social_media_informal_text
    path: social_media_informal_text/tokenizer_robustness_social_media_informal_text-*
  - split: dev
    path: social_media_informal_text/dev-*
  - split: test
    path: social_media_informal_text/test-*
- config_name: temporal_expressions
  data_files:
  - split: tokenizer_robustness_temporal_expressions
    path: temporal_expressions/tokenizer_robustness_temporal_expressions-*
  - split: dev
    path: temporal_expressions/dev-*
  - split: test
    path: temporal_expressions/test-*
dataset_info:
- 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: string
  - name: variation_id
    dtype: string
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: tokenizer_robustness_social_media_informal_text
    num_bytes: 13202
    num_examples: 59
  - name: dev
    num_bytes: 10168
    num_examples: 47
  - name: test
    num_bytes: 13438
    num_examples: 59
  download_size: 35201
  dataset_size: 36808
- 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: string
  - name: variation_id
    dtype: string
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: tokenizer_robustness_temporal_expressions
    num_bytes: 4603
    num_examples: 21
  - name: dev
    num_bytes: 1306
    num_examples: 6
  - name: test
    num_bytes: 4687
    num_examples: 21
  download_size: 23619
  dataset_size: 10596
---

# 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

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

## Uses

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### Direct Use

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### Out-of-Scope Use

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## Dataset Structure

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

## Dataset Creation

### Curation Rationale

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### 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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#### Who are the source data producers?

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### Annotations [optional]

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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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[More Information Needed]

## Bias, Risks, and Limitations

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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]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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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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