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CLARITY: Unmasking Political Question Evasions

SemEval-2026 Task 6 (CLARITY): detecting how directly a politician answers a question. Given a question-answer pair from a U.S. presidential interview, annotators classify the reply into one of three clarity levels (Clear Reply, Ambiguous, Clear Non-Reply) and, when the answer is evasive, identify the evasion technique used. Multi-part questions are first decomposed into single sub-questions so each judgment captures how well one specific inquiry is addressed.

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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
# CLARITY: Unmasking Political Question Evasions
# Based on Thomas, Filandrianos, Lymperaiou, Zerva, and Stamou, SemEval-2026 Task 6
# Paper: https://aclanthology.org/2026.semeval-1.449/
# Task page: https://konstantinosftw.github.io/CLARITY-SemEval-2026/
#
# Given a question-answer (QA) pair from a U.S. presidential interview
# (2006-2023), judge how directly the answer addresses the question. The
# task has two nested subtasks:
#   - Subtask 1 (Clarity): 3 coarse clarity tiers
#   - Subtask 2 (Evasion): one of 9 fine-grained evasion techniques when
#     the answer is not a clear reply
# Multi-part questions are decomposed into single sub-questions so each
# annotation captures how well one specific inquiry is addressed.
#
# Subtask 1 clarity labels (from the official task page):
# - Clear Reply: the answer directly and unambiguously addresses the question
# - Ambiguous: the answer partially addresses it or is unclear
# - Clear Non-Reply: the answer avoids the question
#
# Subtask 2 uses a taxonomy of 9 evasion techniques (e.g. deflection,
# partial answer, declining to answer, attacking the question). This
# showcase collects the technique as free text; consult the task paper for
# the full 9-way label set.

annotation_task_name: "CLARITY - Political Question Evasion"
task_dir: "."

data_files:
  - sample-data.json

item_properties:
  id_key: "id"
  text_key: "answer"

output_annotation_dir: "annotation_output/"
output_annotation_format: "json"

port: 8000
server_name: localhost

annotation_schemes:
  - annotation_type: radio
    name: clarity
    description: "How directly does the answer address the question?"
    labels:
      - "Clear Reply"
      - "Ambiguous"
      - "Clear Non-Reply"
    keyboard_shortcuts:
      "Clear Reply": "1"
      "Ambiguous": "2"
      "Clear Non-Reply": "3"
    tooltips:
      "Clear Reply": "The answer directly and unambiguously addresses the question"
      "Ambiguous": "The answer only partially addresses the question or is unclear"
      "Clear Non-Reply": "The answer avoids or does not address the question"

  - annotation_type: text
    name: evasion_technique
    description: "If the answer is not a Clear Reply, which evasion technique is used? (see task taxonomy of 9 techniques)"
    textarea: false
    required: false
    placeholder: "e.g. deflection, partial answer, declining to answer..."

annotation_instructions: |
  Read the question and the politician's answer. Decide whether the answer
  is a Clear Reply, is Ambiguous, or is a Clear Non-Reply to that specific
  question. If it is not a Clear Reply, note which evasion technique the
  respondent used.

html_layout: |
  <div style="padding: 15px; max-width: 820px; margin: auto;">
    <div style="background: #eff6ff; border: 1px solid #bfdbfe; border-radius: 8px; padding: 14px; margin-bottom: 10px;">
      <strong style="color: #1e40af;">Question:</strong>
      <p style="font-size: 16px; line-height: 1.6; margin: 6px 0 0 0;">{{question}}</p>
    </div>
    <div style="background: #f8fafc; border: 1px solid #e2e8f0; border-radius: 8px; padding: 14px;">
      <strong style="color: #334155;">Answer:</strong>
      <p style="font-size: 16px; line-height: 1.6; margin: 6px 0 0 0;">{{answer}}</p>
    </div>
  </div>

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

Sample Datasample-data.json

json
[
  {
    "id": "clr_001",
    "question": "Will you raise taxes on the middle class next year?",
    "answer": "No, I have said repeatedly that no family earning under $400,000 will see a tax increase."
  },
  {
    "id": "clr_002",
    "question": "Do you support a ceasefire in the conflict?",
    "answer": "What we all want is peace, and I think everyone in this country wants to see stability in the region."
  }
]

// ... and 8 more items

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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/task06-clarity-political-evasion
potato start config.yaml

Dataset & paper

Thomas et al., SemEval 2026 (Task 6)

Citation (BibTeX)

bibtex
@inproceedings{thomas-etal-2026-semeval,
    title = "{S}em{E}val-2026 Task 6: {CLARITY} -- Unmasking Political Question Evasions",
    author = "Thomas, Konstantinos  and Filandrianos, Giorgos  and Lymperaiou, Maria  and Zerva, Chrysoula  and Stamou, Giorgos",
    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-1.449",
    pages = "3704--3715"
}

Details

Annotation Types

radiotext

Domain

NLPPolitical DiscourseSemEval

Use Cases

Question Answering AnalysisDiscourse AnalysisPolitical Communication

Tags

semevalsemeval-2026shared-taskpolitical-discourseevasionquestion-answering

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