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Producing the required amounts of training data for machine learning and NLPtasks often involves human annotators doing very repetitive and monotonouswork. In this paper, we present and evaluate our novel annotation frameworkDALPHI, which facilitates the annotation process by providing the annotatorwith suggestions generated by an automated, active-learning based assistancesystem. In a study with 66 participants, we demonstrate on the exemplary taskof annotating named entities in text documents that with this assistance systemthe annotation processes can be improved with respect to the quality andquantity of produced annotations, even if the pre-annotations provided by theassistance system are at a recall level of only 50%.

The DALPHI annotation framework & how its pre-annotations can improve annotator efficiency