Abstract
Luminoso participated in the SemEval 2018 task on “Capturing Discriminative Attributes” with a system based on ConceptNet, an open knowledge graph focused on general knowledge. In this paper, we describe how we trained a linear classifier on a small number of semantically-informed features to achieve an F1 score of 0.7368 on the task, close to the task’s high score of 0.75.- Anthology ID:
- S18-1162
- Original:
- S18-1162v1
- Version 2:
- S18-1162v2
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Editors:
- Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 985–989
- Language:
- URL:
- https://aclanthology.org/S18-1162
- DOI:
- 10.18653/v1/S18-1162
- Cite (ACL):
- Robyn Speer and Joanna Lowry-Duda. 2018. Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational Knowledge. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 985–989, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational Knowledge (Speer & Lowry-Duda, SemEval 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/S18-1162.pdf
- Code
- LuminosoInsight/semeval-discriminatt
- Data
- ConceptNet