The UCD-Net System at SemEval-2020 Task 1: Temporal Referencing with Semantic Network Distances

Paul Nulty, David Lillis


Abstract
This paper describes the UCD system entered for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection. We propose a novel method based on distance between temporally referenced nodes in a semantic network constructed from a combination of the time specific corpora. We argue for the value of semantic networks as objects for transparent exploratory analysis and visualisation of lexical semantic change, and present an implementation of a web application for the purpose of searching and visualising semantic networks. The results of the change measure used for this task were not among the best performing systems, but further calibration of the distance metric and backoff approaches may improve this method.
Anthology ID:
2020.semeval-1.13
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Editors:
Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
Venue:
SemEval
SIG:
SIGLEX
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
119–125
Language:
URL:
https://aclanthology.org/2020.semeval-1.13
DOI:
10.18653/v1/2020.semeval-1.13
Bibkey:
Cite (ACL):
Paul Nulty and David Lillis. 2020. The UCD-Net System at SemEval-2020 Task 1: Temporal Referencing with Semantic Network Distances. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 119–125, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
The UCD-Net System at SemEval-2020 Task 1: Temporal Referencing with Semantic Network Distances (Nulty & Lillis, SemEval 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.semeval-1.13.pdf