Title
More than just Frequency? Demasking Unsupervised Hypernymy Prediction Methods.
Abstract
This paper presents a comparison of unsupervised methods of hypernymy prediction (i.e., to predict which word in a pair of words such as fish-cod is the hypernym and which the hyponym). Most importantly, we demonstrate across datasets for English and for German that the predictions of three methods (WeedsPrec, invCL, SLQS Row) strongly overlap and are highly correlated with frequency-based predictions. In contrast, the second-order method SLQS shows an overall lower accuracy but makes correct predictions where the others go wrong. Our study once more confirms the general need to check the frequency bias of a computational method in order to identify frequency-(un)related effects.
Year
Venue
DocType
2021
ACL/IJCNLP
Conference
Volume
Citations 
PageRank 
2021.findings-acl
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Thomas Bott100.34
Dominik Schlechtweg227.85
Sabine Schulte im Walde344065.65