Techniques & Methods
Entity Annotation
Entity annotation is the process of manually labeling text with entity tags—marking "London" as LOCATION, "Google" as ORGANIZATION, "Sundar Pichai" as PERSON. High-quality annotated datasets are the primary input for training and evaluating NER models.
Annotation quality directly impacts model quality. Annotation projects use guidelines, multiple annotators with inter-annotator agreement measurement, and adjudication processes to ensure consistency at scale.
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Related Terms
Techniques & Methods
Named Entity Recognition (NER)
Identifying and classifying named entities in text into predefined categories like people and places.
Techniques & Methods
Entity Extraction
Identifying and classifying named entities—people, places, organizations—within text.
Techniques & Methods
Linguistic Annotation
Adding linguistic metadata—such as POS tags, parse trees, or coreferences—to text for analysis.
Miscellaneous
Training Data
The labeled or unlabeled dataset used to fit a model's parameters during the learning process.