--- pretty_name: Macaron tags: - benchmark - evaluation - multilingual - multicultural - reasoning - template-based task_categories: - question-answering - text-classification annotations_creators: - expert-generated language: - en - am - ar - zh - ka - el - hi - id - it - ja - ky - es - pt - yo - tl - zu - th - tr configs: - config_name: MCQ data_files: "macaron_mcq.csv" - config_name: True-False data_files: "macaron_truefalse.csv" - config_name: Templates data_files: "templates_rowshf.csv" --- # Macaron **Macaron** is a controlled, human-written benchmark for **multilingual and multicultural reasoning** created with a **template-first** approach. Each example is **scenario-aligned** across **English** and a **local language**, enabling controlled comparison of reasoning under culturally grounded premises. --- ## At a glance | Configuration | Rows | Description | |--------------|------|-------------| | MCQ | 1,977 | Bilingual multiple-choice questions (English + local language) | | True-False | 3,954 | Bilingual verification statements derived from MCQs | | Templates | 100 | Reusable templates with reasoning and cultural metadata | > Counting each language-specific instance separately (English + local), the benchmark contains **11,862 evaluation instances**. --- ## Supported tasks - Multiple-choice question answering - Binary classification / verification (True/False) --- ## Coverage Macaron provides controlled coverage across **languages, cultural contexts, reasoning types, and cultural aspects**. All instances are **scenario-aligned** across English and a local language. ### Languages and cultural contexts The benchmark spans **20 cultural contexts**, each paired with **English** and one primary local language. | Country / Context | Local language | |------------------|----------------| | Brazil | Brazilian Portuguese | | China | Chinese | | Egypt | Egyptian Arabic | | Ethiopia | Amharic | | Georgia | Georgian | | Greece | Greek | | India | Hindi | | Indonesia | Indonesian | | Italy | Italian | | Japan | Japanese | | Kyrgyzstan | Kyrgyz | | Mexico | Mexican Spanish | | Morocco | Moroccan Arabic | | Nigeria | Yoruba | | Philippines | Tagalog | | South Africa | Zulu | | Thailand | Thai | | Tunisia | Tunisian Arabic | | Turkey | Turkish | | Yemen | Yemeni Arabic | --- ### Dataset size by context Each multiple-choice question (MCQ) produces: - **1 MCQ row** - **2 True-False rows** Each row contains **both English and local-language text**. | Country / Context | MCQ rows | True-False rows | Evaluation instances (EN + Local) | |------------------|----------|-----------------|----------------------------------| | Brazil | 100 | 200 | 600 | | China | 97 | 194 | 582 | | Egypt | 99 | 198 | 594 | | Ethiopia | 98 | 196 | 588 | | Georgia | 99 | 198 | 594 | | Greece | 100 | 200 | 600 | | India | 100 | 200 | 600 | | Indonesia | 95 | 190 | 570 | | Italy | 98 | 196 | 588 | | Japan | 99 | 198 | 594 | | Kyrgyzstan | 100 | 200 | 600 | | Mexico | 99 | 198 | 594 | | Morocco | 100 | 200 | 600 | | Nigeria | 95 | 190 | 570 | | Philippines | 99 | 198 | 594 | | South Africa | 100 | 200 | 600 | | Thailand | 99 | 198 | 594 | | Tunisia | 100 | 200 | 600 | | Turkey | 100 | 200 | 600 | | Yemen | 100 | 200 | 600 | --- ### Reasoning types Each template and derived instance is tagged with one or more **reasoning types**. | Reasoning type | Description | |---------------|-------------| | Mathematical Reasoning | Numerical computation and comparison | | Commonsense Reasoning | Everyday plausibility and typical situations | | Causal Reasoning | Cause–effect relations | | Temporal Reasoning | Time, order, calendars | | Logical Reasoning | Deduction, implication, and analogy | | Spatial Reasoning | Geographic and spatial relations | | Multi-hop Reasoning | Composition of two or more inference steps | --- ### Cultural aspects Templates are tagged with one or more **cultural aspects**, covering **22 domains of everyday life**: - agriculture - brands and commerce - cities and landmarks - death and funerals - education - events and festivals - famous people - fashion and media - folklore and folktales - food and cuisine - language and communication - literature and written works - music and art - naming - objects and units - politics and governance - relationships - social customs - sports - time - transportation - socio-religious aspects of life Both `reasoning_category` and `cultural_aspect` fields are **multi-label**, stored as comma-separated strings in the CSV files. ## Intended use Macaron is intended for: - Zero-shot and few-shot evaluation of multilingual large language models - Cross-lingual robustness analysis using scenario-aligned English and local-language inputs - Diagnostic analysis by reasoning type and cultural domain Not recommended uses: - Training and testing on the same benchmark - Drawing broad conclusions about entire cultures, countries, or languages --- ## How to load ```python from datasets import load_dataset ds_mcq = load_dataset("AlaaAhmed2444/Macaron", "MCQ") ds_tf = load_dataset("AlaaAhmed2444/Macaron", "True-False") ds_tpl = load_dataset("AlaaAhmed2444/Macaron", "Templates") ``` --- ## Ethical considerations and limitations - Cultural coverage is necessarily coarse: each cultural context is represented by one primary local language and does not capture within-country diversity or dialect continua. - The benchmark focuses on controlled reasoning formats (multiple-choice and True/False), which do not reflect open-ended dialogue or interactive reasoning settings. - Results should not be interpreted as representing full cultural or linguistic diversity, but rather as performance on a controlled, template-based evaluation. --- ## Citation If you use Macaron, please cite the accompanying paper: ```bibtex @misc{elsetohy_macaron, title = {Macaron: Controlled, Human-Written Benchmark for Multilingual and Multicultural Reasoning via Template-Filling}, author = {Elsetohy, Alaa and Hadhoud, Sama and Wibowo, Haryo Akbarianto and Whitehouse, Chenxi and Winata, Genta Indra and Koto, Fajri and Aji, Alham Fikri}, note = {will be updated with arXiv link} }