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We introduce a novel data generation method for contradiction detection,which leverages the generative power of large language models as well aslinguistic rules. Our vision is to provide a condensed corpus of prototypicalcontradictions, allowing for in-depth linguistic analysis as well as efficientlanguage model fine-tuning. To this end, we instruct the generative models tocreate contradicting statements with respect to descriptions of specificcontradiction types. In addition, the model is also instructed to come up withcompletely new contradiction typologies. As an auxiliary approach, we uselinguistic rules to construct simple contradictions such as those arising fromnegation, antonymy and numeric mismatch. We find that our methods yieldpromising results in terms of coherence and variety of the data. Furtherstudies, as well as manual refinement are necessary to make use of this data ina machine learning setup.

Generating Prototypes for Contradiction Detection Using Large Language Models and Linguistic Rules