ALB at SemEval-2018 Task 10: A System for Capturing Discriminative Attributes

Bogdan Dumitru, Alina Maria Ciobanu, Liviu P. Dinu


Abstract
Semantic difference detection attempts to capture whether a word is a discriminative attribute between two other words. For example, the discriminative feature red characterizes the first word from the (apple, banana) pair, but not the second. Modeling semantic difference is essential for language understanding systems, as it provides useful information for identifying particular aspects of word senses. This paper describes our system implementation (the ALB system of the NLP@Unibuc team) for the 10th task of the SemEval 2018 workshop, “Capturing Discriminative Attributes”. We propose a method for semantic difference detection that uses an SVM classifier with features based on co-occurrence counts and shallow semantic parsing, achieving 0.63 F1 score in the competition.
Anthology ID:
S18-1158
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:
963–967
Language:
URL:
https://www.aclweb.org/anthology/S18-1158
DOI:
10.18653/v1/S18-1158
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1158.pdf