Named Entity Recognition

Knows NER basics: entity types (PER, ORG, LOC), BIO tagging, basic approaches. Applies pre-trained spaCy NER models and evaluates quality via F1-score.

Independently trains and fine-tunes NER models for domain-specific tasks. Annotates data, configures BIO/BILOU schemes, trains models on spaCy and Hugging Face transformers.

Designs production NER systems: multi-model ensemble, active learning for annotation, nested NER, cross-lingual transfer. Optimizes for high accuracy on domain-specific data.

Defines NER strategy for the team. Establishes guidelines for annotation, model selection, evaluation methodology. Coordinates annotator work and ensures labeling consistency.

Shapes enterprise NER strategy for the organization. Defines unified entity taxonomy, cross-domain NER approaches, and quality assurance standards for all company NER systems.