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paperarXivTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago

ReaORE: Reasoning-Guided Progressive Open Relation Extraction Empowered by Large Reasoning Models

Open Relation Extraction (OpenRE) requires a model to extract unseen relations between head and tail entities from unstructured text for real-world applications. The core challenge of OpenRE lies in achieving reliable generalization to unseen relation types. Current OpenRE approaches either employ clustering techniques, which cannot generate relation labels and suffer from poor generalization, or rely on direct relation label generation via Large Language Models (LLMs), which lack sufficient discriminative capacity to distinguish easily confused relations. To address these limitations, we prop

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  • PossiblePossibly related (embedding) · 48%Tencent/WeKnora
  • FuzzySimilar title/name (fuzzy) · 59%rasbt/reasoning-from-scratch

    Fuzzy title match (0.73): “ReaORE: Reasoning-Guided Progressive Open Relation Extractio” ≈ “rasbt/reasoning-from-scratch”

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