Triple

T22600997
Position Surface form Disambiguated ID Type / Status
Subject Cahn–Hilliard equation E574814 entity
Predicate relatedTo P37 FINISHED
Object Allen–Cahn equation 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: Allen–Cahn equation | Statement: [Cahn–Hilliard equation, relatedTo, Allen–Cahn equation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allen–Cahn equation
Context triple: [Cahn–Hilliard equation, relatedTo, Allen–Cahn equation]
  • A. Cahn–Hilliard equation
    The Cahn–Hilliard equation is a nonlinear partial differential equation that models phase separation and coarsening in binary mixtures and other systems undergoing spinodal decomposition.
  • B. Mullins–Sekerka instability
    The Mullins–Sekerka instability is a morphological instability that occurs during diffusion-limited solidification or crystal growth, leading to pattern formation such as dendrites at moving phase boundaries.
  • C. Stefan problem
    The Stefan problem is a classical mathematical model in heat transfer that describes how phase-change boundaries, such as the interface between ice and water, move over time.
  • D. 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.
  • E. Kardar–Parisi–Zhang equation
    The Kardar–Parisi–Zhang equation is a fundamental stochastic partial differential equation that models the dynamic scaling and roughening of growing interfaces in nonequilibrium statistical physics.
  • 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: Allen–Cahn equation
Target entity description: The Allen–Cahn equation is a reaction–diffusion partial differential equation used to model phase separation and interface motion in multi-phase systems.
  • A. Cahn–Hilliard equation
    The Cahn–Hilliard equation is a nonlinear partial differential equation that models phase separation and coarsening in binary mixtures and other systems undergoing spinodal decomposition.
  • B. Mullins–Sekerka instability
    The Mullins–Sekerka instability is a morphological instability that occurs during diffusion-limited solidification or crystal growth, leading to pattern formation such as dendrites at moving phase boundaries.
  • C. Stefan problem
    The Stefan problem is a classical mathematical model in heat transfer that describes how phase-change boundaries, such as the interface between ice and water, move over time.
  • D. 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.
  • E. Kardar–Parisi–Zhang equation
    The Kardar–Parisi–Zhang equation is a fundamental stochastic partial differential equation that models the dynamic scaling and roughening of growing interfaces in nonequilibrium statistical physics.
  • 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_69e245bc11308190b69d794d5d1e0bb6 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1626c6ce08190b991e89b12c67a5a completed April 29, 2026, 1:44 a.m.
Created at: April 17, 2026, 2:50 p.m.