Collecting high-quality annotations for Natural Language Processing (NLP) tasks poses challenges. Gamified annotation systems, like Games-with-a-Purpose (GWAP), have become popular tools for data annotation. For GWAPs to be effective, they must be user-friendly and produce high-quality annotations to ensure the collected data’s usefulness. This paper investigates the effectiveness of a gamified approach through two specific studies on an existing GWAP designed for collecting NLP coreference judgments. The first study involved preliminary usability testing using the concurrent think-aloud method to gather open-ended feedback. This feedback was crucial in pinpointing design issues. Following this, we conducted semi-structured interviews with our participants, and the insights collected from these interviews were instrumental in crafting player personas, which informed design improvements aimed at enhancing user experience. The outcomes of our research have been generalized to benefit other GWAP implementations. The second study evaluated the linguistic acceptability and reliability of the data collected through our GWAP. Our findings indicate that our GWAP produced reliable corpora with 91.49% accuracy and 0.787 Cohen’s kappa.

Coreference resolution is a key aspect of text comprehension, but the size of the available coreference corpora for Arabic is limited in comparison to the size of the corpora for other languages. In this paper we present a Game-With-A-Purpose called Stroll with a Scroll created to collect from players coreference annotations for Arabic. The key contribution of this work is the embedding of the annotation task in a virtual world setting, as opposed to the puzzle-type games used in previously proposed Games-With-A-Purpose for coreference.