By Wageningen
Discover how domain-specific text corpora and expert-driven annotation practices enable reliable document identification and support trustworthy AI-based relevance classification.
Identifying relevant information within large text archives requires more than automated keyword searches.
This best practice outlines a transparent, reproducible approach to building domain-specific corpora that combine expert judgement with modern AI methods.
Key highlights:
- Domain-specific Corpus Design: Transforms large, general-purpose text archives into focused datasets tailored to a clearly defined thematic domain.
- Expert-driven Annotation: Applies authoritative relevance definitions and structured guidelines to ensure consistent and meaningful labels.
- Uncertainty-aware Labelling: Introduces multi-level labels to capture ambiguous cases instead of forcing binary decisions.
- Quality and Reliability Control: Uses inter-annotator agreement and documented disagreement resolution to strengthen dataset trustworthiness.
- AI-enabled Document Identification: Supports scalable relevance classification using advanced language models while preserving transparency and interpretability.
