Triple

T243751
Position Surface form Disambiguated ID Type / Status
Subject Einstein–Smoluchowski relation E4990 entity
Predicate isSpecialCaseOf P2372 FINISHED
Object fluctuation–dissipation theorem
The fluctuation–dissipation theorem is a fundamental principle in statistical physics that links the random microscopic fluctuations in a system at thermal equilibrium to its macroscopic response to external perturbations.
E31542 NE FINISHED

How this triple was built (4 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: fluctuation–dissipation theorem | Statement: [Einstein–Smoluchowski relation, isSpecialCaseOf, fluctuation–dissipation theorem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: fluctuation–dissipation theorem
Context triple: [Einstein–Smoluchowski relation, isSpecialCaseOf, fluctuation–dissipation theorem]
  • A. Einstein–Smoluchowski relation
    The Einstein–Smoluchowski relation is a fundamental equation in statistical physics that links the diffusion coefficient of particles undergoing Brownian motion to their mobility and thermal energy.
  • B. Fokker–Planck equation
    The Fokker–Planck equation is a partial differential equation that describes the time evolution of the probability density function of a stochastic (random) process, such as Brownian motion.
  • C. Feynman–Hellmann theorem
    The Feynman–Hellmann theorem is a result in quantum mechanics that relates the derivative of an energy eigenvalue with respect to a parameter in the Hamiltonian to the expectation value of the corresponding derivative of the Hamiltonian.
  • D. Langevin dynamics
    Langevin dynamics is a stochastic approach to modeling the motion of particles in a fluid by combining deterministic forces with random thermal fluctuations, often used to simulate Brownian motion and other nonequilibrium processes.
  • E. Huang–Rhys factor
    The Huang–Rhys factor is a dimensionless parameter in solid-state and molecular spectroscopy that quantifies the strength of electron–phonon (vibronic) coupling during electronic transitions.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: fluctuation–dissipation theorem
Triple: [Einstein–Smoluchowski relation, isSpecialCaseOf, fluctuation–dissipation theorem]
Generated description
The fluctuation–dissipation theorem is a fundamental principle in statistical physics that links the random microscopic fluctuations in a system at thermal equilibrium to its macroscopic response to external perturbations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: fluctuation–dissipation theorem
Target entity description: The fluctuation–dissipation theorem is a fundamental principle in statistical physics that links the random microscopic fluctuations in a system at thermal equilibrium to its macroscopic response to external perturbations.
  • A. Einstein–Smoluchowski relation
    The Einstein–Smoluchowski relation is a fundamental equation in statistical physics that links the diffusion coefficient of particles undergoing Brownian motion to their mobility and thermal energy.
  • B. Fokker–Planck equation
    The Fokker–Planck equation is a partial differential equation that describes the time evolution of the probability density function of a stochastic (random) process, such as Brownian motion.
  • C. Feynman–Hellmann theorem
    The Feynman–Hellmann theorem is a result in quantum mechanics that relates the derivative of an energy eigenvalue with respect to a parameter in the Hamiltonian to the expectation value of the corresponding derivative of the Hamiltonian.
  • D. Langevin dynamics
    Langevin dynamics is a stochastic approach to modeling the motion of particles in a fluid by combining deterministic forces with random thermal fluctuations, often used to simulate Brownian motion and other nonequilibrium processes.
  • E. Huang–Rhys factor
    The Huang–Rhys factor is a dimensionless parameter in solid-state and molecular spectroscopy that quantifies the strength of electron–phonon (vibronic) coupling during electronic transitions.
  • F. None of above. chosen

Provenance (5 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_69a257c3d0708190b0871c4269d273e6 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25cef84ac81908fcc175b7f89653b completed Feb. 28, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a36cf2e84c81908d87847d498f96f4 completed Feb. 28, 2026, 10:32 p.m.
NEDg Description generation batch_69a36d68858c81908cc2d2dc94b1a482 completed Feb. 28, 2026, 10:34 p.m.
NED2 Entity disambiguation (via description) batch_69a36dbb7dc88190a75f2c0bbb478ccc completed Feb. 28, 2026, 10:35 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.