English

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

Computation and Language 2018-05-01 v1

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.

Keywords

Cite

@article{arxiv.1804.11251,
  title  = {BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes},
  author = {Enrico Santus and Chris Biemann and Emmanuele Chersoni},
  journal= {arXiv preprint arXiv:1804.11251},
  year   = {2018}
}

Comments

3 tables, 4 pages, SemEval, NAACL, NLP, Task

R2 v1 2026-06-23T01:40:11.451Z