Abstract
This paper describes the SemEval 2018 Task 10 on Capturing Discriminative Attributes. Participants were asked to identify whether an attribute could help discriminate between two concepts. For example, a successful system should determine that urine is a discriminating feature in the word pair kidney,bone. The aim of the task is to better evaluate the capabilities of state of the art semantic models, beyond pure semantic similarity. The task attracted submissions from 21 teams, and the best system achieved a 0.75 F1 score.
Cite
CITATION STYLE
Krebs, A., Lenci, A., & Paperno, D. (2018). SemEval-2018 Task 10: Capturing Discriminative Attributes. In NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop (pp. 732–740). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s18-1117
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