Triple

T23382511
Position Surface form Disambiguated ID Type / Status
Subject Gerhard Huisken E593786 entity
Predicate knownFor P22 FINISHED
Object Huisken’s monotonicity formula NE NERFINISHED

How this triple was built (3 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Huisken’s monotonicity formula | Statement: [Gerhard Huisken, knownFor, Huisken’s monotonicity formula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huisken’s monotonicity formula
Context triple: [Gerhard Huisken, knownFor, Huisken’s monotonicity formula]
  • A. Perelman’s entropy functionals
    Perelman’s entropy functionals are analytic quantities introduced by Grigori Perelman to study the behavior and singularities of the Ricci flow, playing a central role in his proof of the Poincaré and geometrization conjectures.
  • B. Hamilton’s Harnack inequalities for Ricci flow
    Hamilton’s Harnack inequalities for Ricci flow are fundamental differential inequalities that provide monotonicity and curvature control along solutions to the Ricci flow, playing a key role in the analysis of geometric evolution and singularity formation.
  • C. Monge–Ampère equation
    The Monge–Ampère equation is a fully nonlinear partial differential equation central to differential geometry, optimal transport, and several complex variables, often used to study curvature and geometric structures.
  • D. Hamilton’s compactness theorem for Ricci flow
    Hamilton’s compactness theorem for Ricci flow is a fundamental result in geometric analysis that provides conditions under which a sequence of Ricci flows on Riemannian manifolds subconverges to a limiting Ricci flow, enabling powerful compactness and convergence arguments in the study of geometric evolution.
  • E. Hamilton’s program for the Ricci flow
    Hamilton’s program for the Ricci flow is a geometric analysis framework that uses Ricci flow and related tools to systematically deform and analyze Riemannian metrics in order to classify the topology of three-dimensional manifolds.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Huisken’s monotonicity formula
Target entity description: Huisken’s monotonicity formula is a fundamental result in geometric analysis that provides a non-increasing quantity along mean curvature flow, crucial for understanding singularity formation and regularity of evolving hypersurfaces.
  • A. Perelman’s entropy functionals
    Perelman’s entropy functionals are analytic quantities introduced by Grigori Perelman to study the behavior and singularities of the Ricci flow, playing a central role in his proof of the Poincaré and geometrization conjectures.
  • B. Hamilton’s Harnack inequalities for Ricci flow
    Hamilton’s Harnack inequalities for Ricci flow are fundamental differential inequalities that provide monotonicity and curvature control along solutions to the Ricci flow, playing a key role in the analysis of geometric evolution and singularity formation.
  • C. Monge–Ampère equation
    The Monge–Ampère equation is a fully nonlinear partial differential equation central to differential geometry, optimal transport, and several complex variables, often used to study curvature and geometric structures.
  • D. Hamilton’s compactness theorem for Ricci flow
    Hamilton’s compactness theorem for Ricci flow is a fundamental result in geometric analysis that provides conditions under which a sequence of Ricci flows on Riemannian manifolds subconverges to a limiting Ricci flow, enabling powerful compactness and convergence arguments in the study of geometric evolution.
  • E. Hamilton’s program for the Ricci flow
    Hamilton’s program for the Ricci flow is a geometric analysis framework that uses Ricci flow and related tools to systematically deform and analyze Riemannian metrics in order to classify the topology of three-dimensional manifolds.
  • F. None of above. chosen

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e25d268a50819095f2fd479da8ef3f completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a3b9287481908fd86c41f6d9fc53 completed April 29, 2026, 6:22 a.m.
Created at: April 17, 2026, 5:34 p.m.