BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- And Graph-based Information to Identify Discriminative Attributes

N/ACitations
Citations of this article
67Readers
Mendeley users who have this article in their library.

Abstract

This paper describes BomJi, a supervised system for capturing discriminative attributes in word pairs (e.g. yellow as discriminative for banana over watermelon). The system relies on an XGB classifier trained on carefully engineered graph-, pattern- and word embedding-based features. It participated in the SemEval-2018 Task 10 on Capturing Discriminative Attributes, achieving an F1 score of 0.73 and ranking 2nd out of 26 participant systems.

Cite

CITATION STYLE

APA

Santus, E., Biemann, C., & Chersoni, E. (2018). BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- And Graph-based Information to Identify Discriminative Attributes. In NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop (pp. 990–994). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s18-1163

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free