SemEval-2018 Task 10: Capturing Discriminative Attributes

Alicia Krebs, Alessandro Lenci, Denis Paperno


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.
Anthology ID:
S18-1117
Volume:
Proceedings of The 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
732–740
Language:
URL:
https://www.aclweb.org/anthology/S18-1117
DOI:
10.18653/v1/S18-1117
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1117.pdf