Papers › Technical Report: Adjudication of Coreference Annotations via Answer Set Optimization
Technical Report: Adjudication of Coreference Annotations via Answer Set Optimization
Peter Schüller
We describe the first automatic approach for merging coreference annotations obtained from multiple annotators into a single gold standard. This merging is subject to certain linguistic hard constraints and optimization criteria that prefer solutions with minimal divergence from annotators. The representation involves an equivalence relation over a large number of elements. We use Answer Set Programming to describe two representations of the problem and four objective functions suitable for different datasets. We provide two structurally different real-world benchmark datasets based on the METU-Sabanci Turkish Treebank and we report our experiences in using the Gringo, Clasp, and Wasp tools for computing optimal adjudication results on these datasets.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections