entity-labeling-and-ner

# Entity Labeling and NER Use this sub-skill for agricultural entity labeling, THULAC-based NER, and the legacy KNN label-prediction workflow. ## Read when - You need to validate or interpret `term label` files with labels `0-16`. - You need the entity-recognition flow that combines THULAC tags, predicted labels, and Neo4j entity presence checks. - You need to inspect the KNN classifier interface or its fastText prerequisites. - You need to work with manual seed labels or predicted label files. ## Do - Start with [label taxonomy](references/label-taxonomy.md) for the accepted label ids and file formats. - Use [NER and labeling workflow](references/entity-labeling-and-ner.md) for the recognition flow, seed-label generation, and label file lifecycle. - Use [KNN classifier API](references/knn-classifier-api.md) when a task depends on the legacy classifier interface or its prerequisites. - Run [label file check](scripts/label_file_check.py) before trusting a label file. - Run [KNN feature probe](scripts/knn_feature_probe.py) to inspect the non-model prerequisites without downloading the fastText model. ## Do not - Do not treat this sub-skill as the Django UI route owner. - Do not treat this sub-skill as the Neo4j import/query owner. - Do not treat this sub-skill as the relation-sentence labeling owner. - Do not claim live KNN prediction is verified unless the fastText model file and backing graph data are actually present. ## Outputs this sub-skill owns - Numeric agricultural label taxonomy `0-16`. - THULAC + predicted-label NER behavior. - Label-file validation. - KNN feature prerequisites and legacy classifier interface notes. - Manual and seed label workflows. ## Quick checks - `python scripts/label_file_check.py --demo` - `python scripts/knn_feature_probe.py --demo`