Adjudication of coreference annotations via answer set optimisation


Schueller P.

JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, cilt.30, ss.525-546, 2018 (SCI İndekslerine Giren Dergi)

  • Cilt numarası: 30 Konu: 4
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1080/0952813x.2018.1456793
  • Dergi Adı: JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
  • Sayfa Sayısı: ss.525-546

Özet

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 optimisation 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 data-sets. We provide two structurally different real-world benchmark data-sets 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 data-sets.