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Showcase/Everyday Knowledge Across Diverse Languages and Cultures (BLEnD)
intermediateevaluation

Everyday Knowledge Across Diverse Languages and Cultures (BLEnD)

SemEval-2026 Task 7: evaluating everyday cultural knowledge across diverse languages and cultures, built on the BLEnD benchmark. Annotators answer culturally grounded everyday-knowledge questions (e.g. common foods, customs, celebrations) for a given country/region. Two subtasks: Short Answer Questions (SAQ) and Multiple-Choice Questions (MCQ), covering many languages including low-resource ones.

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Configuration Fileconfig.yaml

This Potato config reproduces the annotation task. Save it as config.yaml and run potato start config.yaml to try it.

yaml
# Everyday Knowledge Across Diverse Languages and Cultures (BLEnD)
# Based on Ousidhoum et al., SemEval-2026 Task 7
# Paper: https://aclanthology.org/2026.semeval-1.455/
# Task repo: https://github.com/BLEnD-SemEval2026/SemEval-2026-Task-7
# Underlying dataset: BLEnD (Myung et al., NeurIPS 2024) https://arxiv.org/abs/2406.09948
#
# The task probes everyday cultural knowledge (daily habits, customs,
# foods, celebrations) that is often shared within a culture but rarely
# written down. Questions are grounded in a specific country/region.
# Two subtasks:
#   - Subtask 1 (SAQ): give the short free-text answer expected in that culture
#   - Subtask 2 (MCQ): pick the correct option
# This showcase collects both a short answer and a multiple-choice answer,
# plus an optional applicability judgment.

annotation_task_name: "BLEnD - Everyday Cultural Knowledge"
task_dir: "."

data_files:
  - sample-data.json

item_properties:
  id_key: "id"
  text_key: "question"

output_annotation_dir: "annotation_output/"
output_annotation_format: "json"

port: 8000
server_name: localhost

annotation_schemes:
  - annotation_type: text
    name: short_answer
    description: "Subtask 1 (SAQ): the short answer most people in this culture would give"
    textarea: false
    required: false
    placeholder: "Short answer..."

  - annotation_type: radio
    name: mcq_answer
    description: "Subtask 2 (MCQ): select the correct option"
    labels:
      - "A"
      - "B"
      - "C"
      - "D"
    keyboard_shortcuts:
      "A": "1"
      "B": "2"
      "C": "3"
      "D": "4"

  - annotation_type: radio
    name: applicability
    description: "Does this question have a clear culturally-shared answer for the given region?"
    labels:
      - "Yes"
      - "No / varies too much"

annotation_instructions: |
  Each item shows an everyday-knowledge question grounded in a specific
  country or region, along with multiple-choice options. Provide the short
  answer most people in that culture would give (Subtask 1), select the
  correct multiple-choice option (Subtask 2), and indicate whether the
  question has a clear culturally-shared answer.

html_layout: |
  <div style="padding: 15px; max-width: 820px; margin: auto;">
    <div style="background: #ecfeff; border: 1px solid #a5f3fc; border-radius: 8px; padding: 12px; margin-bottom: 10px;">
      <strong style="color: #155e75;">Region:</strong>
      <span style="margin-left: 8px;">{{region}}</span>
      <span style="color:#64748b; margin-left: 12px;">Language: {{language}}</span>
    </div>
    <div style="background: #f0fdfa; border: 1px solid #99f6e4; border-radius: 8px; padding: 16px; margin-bottom: 8px;">
      <strong style="color: #115e59;">Question:</strong>
      <p style="font-size: 17px; line-height: 1.6; margin: 8px 0 0 0;">{{question}}</p>
    </div>
    <div style="color:#334155; font-size: 15px;">{{options}}</div>
  </div>

allow_all_users: true
instances_per_annotator: 50
annotation_per_instance: 3
allow_skip: true

Sample Datasample-data.json

json
[
  {
    "id": "bln_001",
    "region": "South Korea",
    "language": "Korean",
    "question": "What soup is traditionally eaten on New Year's Day to mark getting a year older?",
    "options": "A) Tteokguk   B) Miyeokguk   C) Kimchi jjigae   D) Samgyetang"
  },
  {
    "id": "bln_002",
    "region": "Mexico",
    "language": "Spanish",
    "question": "What bread is traditionally eaten around the Day of the Dead?",
    "options": "A) Bolillo   B) Pan de muerto   C) Concha   D) Telera"
  }
]

// ... and 8 more items

Get This Design

View on GitHub

Clone or download from the repository

Quick start:

git clone https://github.com/davidjurgens/potato-showcase.git
cd potato-showcase/semeval/2026/task07-blend-cultural-knowledge
potato start config.yaml

Dataset & paper

Ousidhoum et al., SemEval 2026 (Task 7); built on BLEnD (Myung et al., NeurIPS 2024)

Citation (BibTeX)

bibtex
@inproceedings{ousidhoum-etal-2026-semeval,
    title = "{S}em{E}val-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures",
    author = "Ousidhoum, Nedjma  and Myung, Junho  and Perez-Almendros, Carla  and Jin, Jiho  and Keleg, Amr  and Beloucif, Meriem  and Zhou, Yi  and Agerri, Rodrigo  and Araujo, Vladimir  and Baes, Naomi  and Barry, James  and Boisson, Joanne  and Chen, Nancy F.  and de Kock, Christine  and Edwards, Aleksandra  and Fernandez de Landa, Joseba  and Imam, Mohamed Fazli  and Hakami, Huda  and Hsieh, Shu-Kai  and Imperial, Joseph Marvin  and Lee, Roy Ka-Wei  and Liu, Zhengyuan  and Lyu, Chenyang  and Samih, Younes  and Sjons, Johan  and Tan, Bryan  and Ushio, Asahi  and Zheng, Weihua  and Oh, Alice  and Camacho-Collados, Jose",
    booktitle = "Proceedings of the 20th International Workshop on Semantic Evaluation (SemEval-2026)",
    year = "2026",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.semeval-1.455",
    pages = "3823--3837"
}

@inproceedings{myung2024blend,
    title = "{BL}{E}n{D}: A Benchmark for {LLM}s on Everyday Knowledge in Diverse Cultures and Languages",
    author = "Myung, Junho and Lee, Nayeon and Zhou, Yi and Jin, Jiho and Putri, Rifki Afina and Antypas, Dimosthenis and Borkakoty, Hsuvas and Kim, Eunsu and Perez-Almendros, Carla and Ayele, Abinew Ali and Guti{\'e}rrez-Basulto, V{\'i}ctor and Ib{\'a}{\~n}ez-Garc{\'i}a, Yazm{\'i}n and Lee, Hwaran and Muhammad, Shamsuddeen Hassan and Park, Kiwoong and Rzayev, Anar Sabuhi and White, Nina and Yimam, Seid Muhie and Pilehvar, Mohammad Taher and Ousidhoum, Nedjma and Camacho-Collados, Jose and Oh, Alice",
    booktitle = "Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track",
    year = "2024",
    url = "https://arxiv.org/abs/2406.09948"
}

Details

Annotation Types

textradio

Domain

NLPCultural KnowledgeSemEval

Use Cases

Question AnsweringCultural Competence EvaluationMultilingual NLP

Tags

semevalsemeval-2026shared-taskcultural-knowledgemultilingualquestion-answeringblend

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