---
license: cc
multilinguality: multilingual
task_categories:
- multiple-choice
pretty_name: Tokenization Robustness Math
tags:
- multilingual
- tokenization
dataset_info:
- config_name: tokenizer_robustness_completion_math_canonical
  features:
  - name: question
    dtype: string
  - name: choices
    list: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: category
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: string
  - name: variation_id
    dtype: string
  - name: vanilla_cos_sim_to_canonical
    struct:
    - name: CohereLabs/aya-expanse-8b
      dtype: float64
    - name: Qwen/Qwen3-8B
      dtype: float64
    - name: bigscience/bloom
      dtype: float64
    - name: common-pile/comma-v0.1-1t
      dtype: float64
    - name: facebook/xglm-564M
      dtype: float64
    - name: google-bert/bert-base-multilingual-cased
      dtype: float64
    - name: google/byt5-small
      dtype: float64
    - name: google/gemma-2-2b
      dtype: float64
    - name: gpt2
      dtype: float64
    - name: meta-llama/Llama-3.2-1B
      dtype: float64
    - name: microsoft/Phi-3-mini-4k-instruct
      dtype: float64
    - name: mistralai/tekken
      dtype: float64
    - name: tiktoken/gpt-4o
      dtype: float64
    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: float64
  - name: trimmed_cos_sim_to_canonical
    struct:
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      dtype: float64
    - name: Qwen/Qwen3-8B
      dtype: float64
    - name: bigscience/bloom
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    - name: common-pile/comma-v0.1-1t
      dtype: float64
    - name: facebook/xglm-564M
      dtype: float64
    - name: google-bert/bert-base-multilingual-cased
      dtype: float64
    - name: google/byt5-small
      dtype: float64
    - name: google/gemma-2-2b
      dtype: float64
    - name: gpt2
      dtype: float64
    - name: meta-llama/Llama-3.2-1B
      dtype: float64
    - name: microsoft/Phi-3-mini-4k-instruct
      dtype: float64
    - name: mistralai/tekken
      dtype: float64
    - name: tiktoken/gpt-4o
      dtype: float64
    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: float64
  - name: token_counts
    struct:
    - name: CohereLabs/aya-expanse-8b
      dtype: int64
    - name: Qwen/Qwen3-8B
      dtype: int64
    - name: bigscience/bloom
      dtype: int64
    - name: common-pile/comma-v0.1-1t
      dtype: int64
    - name: facebook/xglm-564M
      dtype: int64
    - name: google-bert/bert-base-multilingual-cased
      dtype: int64
    - name: google/byt5-small
      dtype: int64
    - name: google/gemma-2-2b
      dtype: int64
    - name: gpt2
      dtype: int64
    - name: meta-llama/Llama-3.2-1B
      dtype: int64
    - name: microsoft/Phi-3-mini-4k-instruct
      dtype: int64
    - name: mistralai/tekken
      dtype: int64
    - name: tiktoken/gpt-4o
      dtype: int64
    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: int64
  splits:
  - name: test
    num_bytes: 11202
    num_examples: 21
  download_size: 29976
  dataset_size: 11202
- config_name: tokenizer_robustness_completion_math_chinese
  features:
  - name: question
    dtype: string
  - name: choices
    list: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: category
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: string
  - name: variation_id
    dtype: string
  - name: vanilla_cos_sim_to_canonical
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      dtype: float64
    - name: Qwen/Qwen3-8B
      dtype: float64
    - name: bigscience/bloom
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    - name: common-pile/comma-v0.1-1t
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    - name: facebook/xglm-564M
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    - name: google-bert/bert-base-multilingual-cased
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    - name: google/byt5-small
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    - name: google/gemma-2-2b
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    - name: gpt2
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    - name: meta-llama/Llama-3.2-1B
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    - name: microsoft/Phi-3-mini-4k-instruct
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    - name: mistralai/tekken
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    - name: tiktoken/gpt-4o
      dtype: float64
    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: float64
  - name: trimmed_cos_sim_to_canonical
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    - name: Qwen/Qwen3-8B
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    - name: bigscience/bloom
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    - name: common-pile/comma-v0.1-1t
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    - name: facebook/xglm-564M
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    - name: google-bert/bert-base-multilingual-cased
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    - name: google/byt5-small
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    - name: google/gemma-2-2b
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    - name: gpt2
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    - name: meta-llama/Llama-3.2-1B
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    - name: microsoft/Phi-3-mini-4k-instruct
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    - name: mistralai/tekken
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    - name: tiktoken/gpt-4o
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    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: float64
  - name: token_counts
    struct:
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      dtype: int64
    - name: Qwen/Qwen3-8B
      dtype: int64
    - name: bigscience/bloom
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    - name: common-pile/comma-v0.1-1t
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    - name: facebook/xglm-564M
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    - name: google-bert/bert-base-multilingual-cased
      dtype: int64
    - name: google/byt5-small
      dtype: int64
    - name: google/gemma-2-2b
      dtype: int64
    - name: gpt2
      dtype: int64
    - name: meta-llama/Llama-3.2-1B
      dtype: int64
    - name: microsoft/Phi-3-mini-4k-instruct
      dtype: int64
    - name: mistralai/tekken
      dtype: int64
    - name: tiktoken/gpt-4o
      dtype: int64
    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: int64
  splits:
  - name: test
    num_bytes: 11147
    num_examples: 21
  download_size: 34445
  dataset_size: 11147
- config_name: tokenizer_robustness_completion_math_decorative_unicode
  features:
  - name: question
    dtype: string
  - name: choices
    list: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: category
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: string
  - name: variation_id
    dtype: string
  - name: vanilla_cos_sim_to_canonical
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      dtype: float64
    - name: Qwen/Qwen3-8B
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    - name: bigscience/bloom
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    - name: common-pile/comma-v0.1-1t
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    - name: facebook/xglm-564M
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    - name: google-bert/bert-base-multilingual-cased
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    - name: google/byt5-small
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    - name: google/gemma-2-2b
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    - name: gpt2
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    - name: meta-llama/Llama-3.2-1B
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    - name: microsoft/Phi-3-mini-4k-instruct
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    - name: mistralai/tekken
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    - name: tiktoken/gpt-4o
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    - name: tokenmonster/englishcode-32000-consistent-v1
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  - name: trimmed_cos_sim_to_canonical
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    - name: Qwen/Qwen3-8B
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    - name: bigscience/bloom
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    - name: google/byt5-small
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    - name: microsoft/Phi-3-mini-4k-instruct
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    - name: mistralai/tekken
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    - name: tiktoken/gpt-4o
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    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: float64
  - name: token_counts
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      dtype: int64
    - name: Qwen/Qwen3-8B
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    - name: bigscience/bloom
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    - name: google/byt5-small
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    - name: google/gemma-2-2b
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    - name: gpt2
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    - name: meta-llama/Llama-3.2-1B
      dtype: int64
    - name: microsoft/Phi-3-mini-4k-instruct
      dtype: int64
    - name: mistralai/tekken
      dtype: int64
    - name: tiktoken/gpt-4o
      dtype: int64
    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: int64
  splits:
  - name: test
    num_bytes: 11986
    num_examples: 21
  download_size: 34660
  dataset_size: 11986
- config_name: tokenizer_robustness_completion_math_farsi
  features:
  - name: question
    dtype: string
  - name: choices
    list: string
  - name: answer
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  - name: answer_label
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  - name: split
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  - name: subcategories
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  - name: category
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  - name: lang
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  - name: second_lang
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  - name: notes
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  - name: id
    dtype: string
  - name: set_id
    dtype: string
  - name: variation_id
    dtype: string
  - name: vanilla_cos_sim_to_canonical
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    - name: Qwen/Qwen3-8B
      dtype: float64
    - name: bigscience/bloom
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    - name: common-pile/comma-v0.1-1t
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    - name: facebook/xglm-564M
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    - name: google-bert/bert-base-multilingual-cased
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    - name: google/byt5-small
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    - name: google/gemma-2-2b
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    - name: gpt2
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    - name: microsoft/Phi-3-mini-4k-instruct
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    - name: mistralai/tekken
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    - name: tiktoken/gpt-4o
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    - name: tokenmonster/englishcode-32000-consistent-v1
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    - name: Qwen/Qwen3-8B
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    - name: bigscience/bloom
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    - name: common-pile/comma-v0.1-1t
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    - name: facebook/xglm-564M
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    - name: google-bert/bert-base-multilingual-cased
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    - name: google/byt5-small
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    - name: google/gemma-2-2b
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    - name: gpt2
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    - name: meta-llama/Llama-3.2-1B
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    - name: microsoft/Phi-3-mini-4k-instruct
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    - name: mistralai/tekken
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    - name: tiktoken/gpt-4o
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    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: float64
  - name: token_counts
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      dtype: int64
    - name: Qwen/Qwen3-8B
      dtype: int64
    - name: bigscience/bloom
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    - name: common-pile/comma-v0.1-1t
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    - name: gpt2
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    - name: microsoft/Phi-3-mini-4k-instruct
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    - name: mistralai/tekken
      dtype: int64
    - name: tiktoken/gpt-4o
      dtype: int64
    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: int64
  splits:
  - name: test
    num_bytes: 12034
    num_examples: 21
  download_size: 34859
  dataset_size: 12034
- config_name: tokenizer_robustness_completion_math_italian
  features:
  - name: question
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  - name: choices
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    - name: tokenmonster/englishcode-32000-consistent-v1
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  - name: token_counts
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    - name: microsoft/Phi-3-mini-4k-instruct
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    - name: mistralai/tekken
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    - name: tiktoken/gpt-4o
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    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: int64
  splits:
  - name: test
    num_bytes: 11219
    num_examples: 21
  download_size: 34631
  dataset_size: 11219
- config_name: tokenizer_robustness_completion_math_latex
  features:
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    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: float64
  - name: token_counts
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    - name: Qwen/Qwen3-8B
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    - name: bigscience/bloom
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    - name: microsoft/Phi-3-mini-4k-instruct
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    - name: mistralai/tekken
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    - name: tiktoken/gpt-4o
      dtype: int64
    - name: tokenmonster/englishcode-32000-consistent-v1
      dtype: int64
  splits:
  - name: test
    num_bytes: 11494
    num_examples: 21
  download_size: 34230
  dataset_size: 11494
- config_name: tokenizer_robustness_completion_math_space_removal
  features:
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  - name: choices
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configs:
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  data_files:
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    path: tokenizer_robustness_completion_math_canonical/test-*
- config_name: tokenizer_robustness_completion_math_chinese
  data_files:
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- config_name: tokenizer_robustness_completion_math_decorative_unicode
  data_files:
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    path: tokenizer_robustness_completion_math_decorative_unicode/test-*
- config_name: tokenizer_robustness_completion_math_farsi
  data_files:
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    path: tokenizer_robustness_completion_math_farsi/test-*
- config_name: tokenizer_robustness_completion_math_italian
  data_files:
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    path: tokenizer_robustness_completion_math_italian/test-*
- config_name: tokenizer_robustness_completion_math_latex
  data_files:
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    path: tokenizer_robustness_completion_math_latex/test-*
- config_name: tokenizer_robustness_completion_math_space_removal
  data_files:
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    path: tokenizer_robustness_completion_math_space_removal/test-*
- config_name: tokenizer_robustness_completion_math_spelled_out
  data_files:
  - split: test
    path: tokenizer_robustness_completion_math_spelled_out/test-*
- config_name: tokenizer_robustness_completion_math_turkish
  data_files:
  - split: test
    path: tokenizer_robustness_completion_math_turkish/test-*
---

# Dataset Card for Tokenization Robustness Math

<!-- 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 text completion 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

<!-- 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. -->

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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]

<!-- 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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#### Who are the annotators?

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#### 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]

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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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