It is a Bird Therefore it is a Robin: On BERT's Internal Consistency Between Hypernym Knowledge and Logical Words

Abstract

The lexical knowledge of NLP systems should be tested (i) for their internal consistency (avoiding groundedness issues) and (ii) both for content words and logical words. In this paper we propose a new method to test the understanding of the hypernymy relationship by measuring its antisymmetry according to the models. Previous studies often rely only on the direct question (e.g., A robin is a...), where we argue a correct answer could only rely on col-locational cues, rather than hierarchical cues. We show how to control for this, and how it is important. We develop a method to ask similar questions about logical words that encode an entailment-like relation (e.g., because or therefore). Our results show important weaknesses of BERT-like models on these semantic tasks.