Annotointiohjeet

Annotointiohjeet, or annotation guidelines, are a document set that describes how data should be labeled for research and development in data science and artificial intelligence. They specify the task objective, the data domain, and the labeling scheme to ensure consistent annotations across annotators and over time.

A typical guideline outlines the label set, with precise definitions, inclusions, exclusions, and examples. It provides decision rules for ambiguous cases and instructions for handling missing or uncertain labels. It may also define the expected granularity, ordering, and format of the annotations, as well as the allowed annotations and disallowed practices. The document often includes training materials, reference examples, and criteria for flagging inconsistent labeling.

The annotation workflow described in guidelines usually covers instructions for annotator selection and training, pilot labeling, quality assurance, adjudication, and versioning. It may specify metrics for intercoder agreement and procedures for updating the guidelines when issues arise.

Guidelines are widely used in fields such as natural language processing, computer vision, and audio processing. They support reproducibility, enable error analysis, and facilitate documentation and auditing. Ethical and privacy considerations are commonly addressed, including how to handle sensitive information, consent, and anonymization.