Annoterer

Annoterer is the Norwegian verb meaning “to annotate.” The form annoterer is the present tense, third-person singular: it describes the act of adding annotations to data, text, or media. In practice, annotation involves attaching notes, metadata, or markup that clarifies content, identifies features, or provides interpretive information. The word itself derives from the Latin annotare, meaning to note or mark.

Annotation is used across disciplines and applications. In linguistics, annotators label parts of speech, syntactic structures, or semantic roles. In digital humanities, texts may be annotated for scholarly commentary, glosses, or editorial notes. In data science and machine learning, annotators label images, audio, or video to create training datasets, for example by drawing bounding boxes or assigning category labels. Annotations also appear in scholarly editions, medical records, and standardized metadata schemes.

The annotation process typically involves defining clear guidelines, selecting or creating an annotation scheme, and then applying labels consistently. Quality control methods include calibration sessions and measuring inter-annotator agreement to assess consistency. Ethical considerations—such as privacy, bias, and consent—are important when annotating personal or sensitive data.

Common formats and tools support annotation, ranging from manual markup in text editors and TEI-encoded documents to specialized labeling software and machine-learning platforms. Annotations enable improved search, data interoperability, and richer analysis by providing structured, interpretable information about raw materials.