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When annotators label data, a key metric for quality assurance isinter-annotator agreement (IAA): the extent to which annotators agree on theirlabels. Though many IAA measures exist for simple categorical and ordinallabeling tasks, relatively little work has considered more complex labelingtasks, such as structured, multi-object, and free-text annotations.Krippendorff's alpha, best known for use with simpler labeling tasks, does havea distance-based formulation with broader applicability, but little work hasstudied its efficacy and consistency across complex annotation tasks.  We investigate the design and evaluation of IAA measures for complexannotation tasks, with evaluation spanning seven diverse tasks: image boundingboxes, image keypoints, text sequence tagging, ranked lists, free texttranslations, numeric vectors, and syntax trees. We identify the difficulty ofinterpretability and the complexity of choosing a distance function as keyobstacles in applying Krippendorff's alpha generally across these tasks. Wepropose two novel, more interpretable measures, showing they yield moreconsistent IAA measures across tasks and annotation distance functions.

Measuring Annotator Agreement Generally across Complex Structured, Multi-object, and Free-text Annotation Tasks