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New French dataset FOLLIE links sentences to first-order logic for NLI

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced FOLLIE, a new dataset designed to bridge French sentences with their first-order logic representations for automated natural language inference. This resource comprises nearly 20,000 inference records and over 36,000 sentence-to-formula mappings, generated using a neural-symbolic pipeline with LLM assistance. Experiments with FOLLIE have demonstrated significant improvements in derivation coverage, and an automatic inference engine built on this dataset achieves accuracies ranging from 65% to 71% on various French NLI tasks. AI

IMPACT Enables more robust automated reasoning over French text, potentially improving NLI systems.

RANK_REASON The item describes a new dataset and associated research paper for natural language inference. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New French dataset FOLLIE links sentences to first-order logic for NLI

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The item describes a new dataset and associated research paper for natural language inference. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Maximos Skandalis ·

    FOLLIE: Automated Reasoning over the First Dataset of Sentences with their First-Order Logical Representation for French

    arXiv:2611.02129v1 Announce Type: new Abstract: FOLLIE (for First-Order Logic for Language Inference and Entailment for French) connects French sentences, compositional first-order representations and automated natural language inference (NLI). The first French NLI-ready, NL-to-F…

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