How do you calculate NER?

Named Entity Recognition (NER) is typically evaluated using metrics such as Precision, Recall, and F1-score. Precision measures the proportion of correctly identified entities out of all entities identified, while Recall measures the proportion of correctly identified entities out of all actual entities present in the text. The F1-score, the harmonic mean of Precision and Recall, provides a single metric that balances both. To compute these, you compare the predicted entities against a set of annotated ground truth entities in a dataset.