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Datasets:
HAERAE-HUB
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NOLLI

Tasks:
Question Answering
Modalities:
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Formats:
parquet
Languages:
Korean
English
Size:
1K - 10K
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Tags:
reasoning
logic
puzzles
korean
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NOLLI / README.md
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Dasool
docs: clarify that yacht_dice is graded on a partial sum, not the 12-round total (#2)
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metadata 
license: mit
language:
  - ko
  - en
pretty_name: NOLLI
size_categories:
  - 1K<n<10K
task_categories:
  - question-answering
tags:
  - reasoning
  - logic
  - puzzles
  - korean
configs:
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    data_files:
      - split: test
        path: array_formula/test-*
  - config_name: causal_dag
    data_files:
      - split: test
        path: causal_dag/test-*
  - config_name: cipher
    data_files:
      - split: test
        path: cipher/test-*
  - config_name: cryptarithmetic
    data_files:
      - split: test
        path: cryptarithmetic/test-*
  - config_name: inequality
    data_files:
      - split: test
        path: inequality/test-*
  - config_name: jamo
    data_files:
      - split: test
        path: jamo/test-*
  - config_name: kinship
    data_files:
      - split: test
        path: kinship/test-*
  - config_name: korean_units
    data_files:
      - split: test
        path: korean_units/test-*
  - config_name: minesweeper
    data_files:
      - split: test
        path: minesweeper/test-*
  - config_name: number_baseball
    data_files:
      - split: test
        path: number_baseball/test-*
  - config_name: saju
    data_files:
      - split: test
        path: saju/test-*
  - config_name: sat_puzzles
    data_files:
      - split: test
        path: sat_puzzles/test-*
  - config_name: sudoku
    data_files:
      - split: test
        path: sudoku/test-*
  - config_name: time
    data_files:
      - split: test
        path: time/test-*
  - config_name: yacht_dice
    data_files:
      - split: test
        path: yacht_dice/test-*
dataset_info:
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        dtype: string
      - name: task
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      - name: language
        dtype: string
      - name: difficulty
        dtype: string
      - name: question
        dtype: string
      - name: answer
        dtype: string
      - name: solution
        dtype: string
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  - config_name: causal_dag
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      - name: task
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      - name: language
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      - name: difficulty
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      - name: question
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      - name: answer
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      - name: solution
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      - name: task
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      - name: language
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      - name: difficulty
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      - name: question
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      - name: answer
        dtype: string
      - name: solution
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  - config_name: cryptarithmetic
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      - name: language
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      - name: difficulty
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      - name: answer
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      - name: solution
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      - name: language
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      - name: difficulty
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      - name: question
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      - name: answer
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      - name: solution
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  - config_name: jamo
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      - name: task
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      - name: language
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      - name: difficulty
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      - name: question
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      - name: answer
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      - name: solution
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  - config_name: kinship
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      - name: task
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      - name: language
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      - name: difficulty
        dtype: string
      - name: question
        dtype: string
      - name: choices
        dtype: string
      - name: answer
        dtype: string
      - name: solution
        dtype: string
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    download_size: 496080
    dataset_size: 3188738
  - config_name: korean_units
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      - name: id
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      - name: task
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      - name: language
        dtype: string
      - name: difficulty
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      - name: question
        dtype: string
      - name: answer
        dtype: string
      - name: solution
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      - name: task
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      - name: language
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      - name: difficulty
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      - name: answer
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      - name: solution
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  - config_name: number_baseball
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      - name: task
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      - name: language
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      - name: difficulty
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      - name: answer
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      - name: solution
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  - config_name: saju
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      - name: task
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      - name: language
        dtype: string
      - name: difficulty
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      - name: answer
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      - name: solution
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      - name: task
        dtype: string
      - name: language
        dtype: string
      - name: difficulty
        dtype: string
      - name: question
        dtype: string
      - name: answer
        dtype: string
      - name: solution
        dtype: string
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  - config_name: sudoku
    features:
      - name: id
        dtype: string
      - name: task
        dtype: string
      - name: language
        dtype: string
      - name: difficulty
        dtype: string
      - name: question
        dtype: string
      - name: answer
        dtype: string
      - name: solution
        dtype: string
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      - name: id
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      - name: task
        dtype: string
      - name: language
        dtype: string
      - name: difficulty
        dtype: string
      - name: question
        dtype: string
      - name: answer
        dtype: string
      - name: solution
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        num_examples: 300
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  - config_name: yacht_dice
    features:
      - name: id
        dtype: string
      - name: task
        dtype: string
      - name: language
        dtype: string
      - name: difficulty
        dtype: string
      - name: question
        dtype: string
      - name: answer
        dtype: string
      - name: solution
        dtype: string
    splits:
      - name: test
        num_bytes: 2112133
        num_examples: 600
    download_size: 374101
    dataset_size: 2112133

NOLLI

NOLLI (논리) is a benchmark of rule-based logical puzzles in Korean and English, designed with difficulty calibration in mind. It covers 15 task types x 3 difficulty tiers (easy / medium / hard) x 100 examples each, for a total of 7,500 examples (EN 3,000 + KO 4,500).

All examples are programmatically generated with solver-verified answers. If you need more data, the generators in the GitHub repository can produce additional examples for any task, language, and difficulty tier.

📄 Paper: https://arxiv.org/abs/2608.04397
💻 Code: https://github.com/HAE-RAE/NOLLI

Tasks

Tasks follow a three-level cross-lingual spectrum: direct translations, script adaptations, and Korean-only tasks.

1. Direct Translations (8 tasks · EN + KO)

Same generators and parameters in both languages, so performance gaps isolate presentation language.

task description en (easy/med/hard) ko (easy/med/hard) total
array_formula Apply row/column aggregation formulas (SUM/MEAN/MAX/...) to a 2D array in sequence 100 / 100 / 100 100 / 100 / 100 600
causal_dag Infer event-propagation time through a causal graph with per-edge delays 100 / 100 / 100 100 / 100 / 100 600
inequality CSP: place numbers 1..N satisfying inequality constraints (unique solution) 100 / 100 / 100 100 / 100 / 100 600
minesweeper Minesweeper with minimal hints preserving a unique solution 100 / 100 / 100 100 / 100 / 100 600
number_baseball Infer a hidden N-digit number from Strike/Ball hints 100 / 100 / 100 100 / 100 / 100 600
sat_puzzles Boolean satisfiability (CNF) framed as a natural-language scenario 100 / 100 / 100 100 / 100 / 100 600
sudoku 9x9 Sudoku with guaranteed-unique solutions 100 / 100 / 100 100 / 100 / 100 600
yacht_dice Assign 12 dice rolls to 12 scoring categories to maximize total score; report the partial sum over spot-checked rounds 100 / 100 / 100 100 / 100 / 100 600

2. Script Adaptations (2 tasks · EN + KO)

Not translation-equivalent: English uses Roman letters; Korean uses Hangul jamo. Calibrated independently per language.

task description en (easy/med/hard) ko (easy/med/hard) total
cipher Decode stacked ciphers (Substitution, Vigenere, Reverse, Playfair, Transposition) 100 / 100 / 100 100 / 100 / 100 600
cryptarithmetic Letters-for-digits arithmetic (SEND+MORE=MONEY style); Korean maps jamo groups 100 / 100 / 100 100 / 100 / 100 600

3. Korean-Only (5 tasks · KO)

No English counterpart — built on structures specific to the Korean language and culture (kinship terminology, the sexagenary calendar, traditional units, Hangul orthography).

task description ko (easy/med/hard) total
jamo Decompose a Hangul syllable into 초성/중성/종성, shift 초성, recompose 100 / 100 / 100 300
kinship Infer a Korean kinship term from a chain of family relationships (26-way multiple choice) 100 / 100 / 100 300
korean_units Convert traditional Korean units (평·마지기·되·자·냥, ...) with randomized rates 100 / 100 / 100 300
saju Compute the four 사주(四柱) pillars from a birth date/time 100 / 100 / 100 300
time Korean calendar reasoning: holiday anchor + relative-day expression → date / 60갑자 일진 100 / 100 / 100 300

Usage 

from datasets import load_dataset

# one task
ds = load_dataset("HAERAE-HUB/NOLLI", "sudoku", split="test")

# filter by language / difficulty (both are columns)
ko_hard = ds.filter(lambda x: x["language"] == "ko" and x["difficulty"] == "hard")

Structure

Each config corresponds to one task. All configs share a single test split and the same schema (the choices column exists only in kinship):

column type description
id str unique example id, e.g. sudoku_ko_0000
task str task name (same as config name)
language str ko or en
difficulty str easy / medium / hard
question str full prompt for the model
choices str JSON-encoded answer choices — only present in the kinship config
answer str gold answer
solution str step-by-step reference solution

Citation 

@misc{choi2026nolli,
      title={NOLLI: A Difficulty-Calibrated Puzzle Benchmark for Diagnosing the English-Korean Performance Gap},
      author={Dasol Choi and Joonyong Park and Daegon Yu and Soo Yong Kim and Youngsook Song and Seunghyeok Hong},
      year={2026},
      eprint={2608.04397},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2608.04397},
}