FOLLIE: Automated Reasoning over the First Dataset of Sentences with their First-Order Logical Representation for French
Read the original on arXiv Computation and Language →FOLLIE is a new French natural language inference resource that links sentences to compositional first‑order logic representations, comprising 19,983 inference records and 36,987 sentence‑slot‑formula mappings derived from six heterogeneous NLI sources. The dataset’s silver annotations are generated by a neural‑symbolic pipeline, including 111 LLM‑assisted additions, and the construction integrates morphosyntactic analysis, probabilistic tagging, grammatical proof search, discourse representation, and first‑order semantic construction. An automated inference engine built on Prover9 and Mace4 achieves up to 71.35% accuracy on SICK‑FR, with high agreement rates on committed decisions, illustrating the resource’s utility for studying deductive inference in French.
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