SemEval 2026 Task 6 (CLARITY)
Political Question Evasion Detection
SemEval 2026 Task 6: CLARITY - Political Question Evasion Detection
Purdue University Fort Wayne, 2026
Participating in SemEval 2026 Task 6 focused on detecting when politicians evade questions during interviews and debates. This task involves identifying instances where responses do not directly address the questions posed, which is crucial for political discourse analysis and media accountability.
Task Overview
The CLARITY task aims to automatically detect question evasion in political discourse by:
- Binary Classification: Determining whether a response addresses the question or evades it
- Evasion Type Identification: Classifying specific evasion strategies employed
- Cross-domain Generalization: Testing models across different political contexts and media formats
Approach
- Transformer-based models for understanding question-response alignment
- Semantic similarity and pragmatic analysis techniques
- Cross-attention mechanisms to model question-answer relationships
- Fine-tuning on political discourse datasets
Relevance
This work connects to broader interests in:
- Evaluating language model behavior in politically sensitive contexts
- Understanding how models handle indirect or evasive language
- Building tools for media literacy and political accountability
Skills & Tools
Python, Transformers, NLP, Political Discourse Analysis, Question-Answering Systems