Overview of GenSIE at IberLEF 2026: Schema-Guided Information Extraction with Small Language Models in Spanish

Resumen

GenSIE is the IberLEF 2026 shared task on schema-guided information extraction from Spanish text with small language models. A CPU-only system receives a (text, instruction, JSON schema) triple and must emit a schema-conformant object faithful to the text, returning null for fields the text does not support. We contribute a 271-instance Spanish development benchmark over eight domains, a 145-instance held-out gold test set that adds a ninth, a semi-automatic agentic curation pipeline with three human gates, and an evaluator pairing micro-F1 over flattened schemas with a multi-model gap-closed metric. Eleven teams submitted thirty-five pipelines, scored on 125 instances against no-think baselines (Gemma 4 E4B F1=0.7780, Qwen3-14B F1=0.7542). DRILLER leads, closing 27.7% of the baseline-to-perfect gap, though a paired bootstrap cannot separate the top three. Retrieval and schema enrichment pay off; extra inference passes do not.