Discriminator at SemEval-2018 Task 10: Minimally Supervised Discrimination

Artur Kulmizev, Mostafa Abdou, Vinit Ravishankar, Malvina Nissim


Abstract
We participated to the SemEval-2018 shared task on capturing discriminative attributes (Task 10) with a simple system that ranked 8th amongst the 26 teams that took part in the evaluation. Our final score was 0.67, which is competitive with the winning score of 0.75, particularly given that our system is a zero-shot system that requires no training and minimal parameter optimisation. In addition to describing the submitted system, and discussing the implications of the relative success of such a system on this task, we also report on other, more complex models we experimented with.
Anthology ID:
S18-1167
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:
1008–1012
Language:
URL:
https://www.aclweb.org/anthology/S18-1167
DOI:
10.18653/v1/S18-1167
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1167.pdf