Probing Neural Language Models for Human Tacit Assumptions

Understand

Humans carry stereotypic tacit assumptions (STAs) (Prince, 1978), or propositional beliefs about generic concepts.

• Such associations are crucial for understanding natural language.
• We construct a diagnostic set of word prediction prompts to evaluate whether recent neural contextualized language models trained on large text corpora capture STAs.
• Our prompts are based on human responses in a psychological study of conceptual associations.