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Guide to: Text Annotation Aggregation

Overview

This article lays out the details of how aggregation works for a Text Annotation job.

šŸ’” Note: Aggregation is currently NOT supported in the Non-Tokenized version of the tool.

Aggregation="tagg"

This is an aggregation method made specially for Text Annotation jobs. This method returns a link to a JSON that describes the text, tokens, spans, and each labeled span will get an inter-annotator agreement score titled "confidence".

The ā€œconfidenceā€ score is calculated by dividing the sum of trust scores of contributors who annotated a particular span by the total number of contributors who worked on that row.

Example

  1. Contributor 1 has a trust of 0.95 and selected token ā€œAppleā€ with class ā€œBrandā€
  2. Contributor 2 has a trust of 0.92 and selected token ā€œAppleā€ with class ā€œBrandā€
  3. Contributor 3 has a trust of 0.82 and selected token ā€œAppleā€ with class ā€œBrandā€
  4. Contributor 4 has a trust of 0.91 and selected token ā€œAppleā€ with class ā€œFruitā€

The aggregated result for the token ā€œAppleā€ would be theĀ class ā€œBrandā€. The confidence score for this span would be:

(0.95+0.92+0.82) / 4 = 0.6725

Important Notes:

  • Spans with attribute ā€œannotated_by = ā€˜machineā€™ā€ are not taken into the equation.
  • In the scenario where test questions are not used, each contributor working in the job would have a trust score of 1.

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