Composing Conversational Negation
This work addresses a fundamental problem in natural language processing for AI systems, but it appears incremental as it builds directly on prior research.
The paper tackles the challenge of modeling natural language negation by extending a previous framework to account for compositional structure, enabling the negation of sentences from single words and handling evolving word meanings.
Negation in natural language does not follow Boolean logic and is therefore inherently difficult to model. In particular, it takes into account the broader understanding of what is being negated. In previous work, we proposed a framework for the negation of words that accounts for 'worldly context'. This paper extends that proposal now accounting for the compositional structure inherent in language within the DisCoCirc framework. We compose the negations of single words to capture the negation of sentences. We also describe how to model the negation of words whose meanings evolve in the text.