Kontrast

Kontrast framework detects cross-modal knowledge inconsistencies across text, tables, and knowledge graphs

Researchers introduce Kontrast, an automatic framework for detecting and categorizing knowledge inconsistencies between Wikipedia text, tables, and Wikidata knowledge graphs. The system uses Text-to-SPARQL and LLM reasoning to compare table-based answers against KG evidence, revealing conflicts, temporal mismatches, and structural gaps. Experiments on Table-QA datasets show cross-modal inconsistencies are common and informative, with implications for RAG pipelines and LLM pre-training data quality. Code and data are publicly released alongside a benchmark for future cross-modal consistency work.