Triple

T2126272
Position Surface form Disambiguated ID Type / Status
Subject Boltzmann equation E46431 entity
Predicate includesOperator P28828 FINISHED
Object Boltzmann collision operator
The Boltzmann collision operator is the nonlinear integral term in kinetic theory that models how particle collisions change the distribution of molecular velocities in a gas.
E236562 NE FINISHED

How this triple was built (5 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: Boltzmann collision operator | Statement: [Boltzmann equation, includesOperator, Boltzmann collision operator]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boltzmann collision operator
Context triple: [Boltzmann equation, includesOperator, Boltzmann collision operator]
  • A. Boltzmann equation
    The Boltzmann equation is a fundamental kinetic theory equation that describes the statistical behavior and time evolution of a dilute gas or particle distribution in phase space due to streaming and collisions.
  • B. Smoluchowski coagulation equation
    The Smoluchowski coagulation equation is a fundamental integro-differential equation in statistical physics that models how particles undergoing random collisions aggregate over time into larger clusters.
  • C. Maxwell–Boltzmann statistics
    Maxwell–Boltzmann statistics is a classical statistical framework in physics that describes the distribution of speeds or energies among distinguishable, non-quantum particles in thermal equilibrium.
  • D. 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.
  • E. Boltzmann distribution
    The Boltzmann distribution is a fundamental probability distribution in statistical mechanics that describes how particles or states are populated over different energy levels at thermal equilibrium.
  • 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: Boltzmann collision operator
Triple: [Boltzmann equation, includesOperator, Boltzmann collision operator]
Generated description
The Boltzmann collision operator is the nonlinear integral term in kinetic theory that models how particle collisions change the distribution of molecular velocities in a gas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Boltzmann collision operator
Target entity description: The Boltzmann collision operator is the nonlinear integral term in kinetic theory that models how particle collisions change the distribution of molecular velocities in a gas.
  • A. Boltzmann equation
    The Boltzmann equation is a fundamental kinetic theory equation that describes the statistical behavior and time evolution of a dilute gas or particle distribution in phase space due to streaming and collisions.
  • B. Smoluchowski coagulation equation
    The Smoluchowski coagulation equation is a fundamental integro-differential equation in statistical physics that models how particles undergoing random collisions aggregate over time into larger clusters.
  • C. Maxwell–Boltzmann statistics
    Maxwell–Boltzmann statistics is a classical statistical framework in physics that describes the distribution of speeds or energies among distinguishable, non-quantum particles in thermal equilibrium.
  • D. 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.
  • E. Boltzmann distribution
    The Boltzmann distribution is a fundamental probability distribution in statistical mechanics that describes how particles or states are populated over different energy levels at thermal equilibrium.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: includesOperator
Context triple: [Boltzmann equation, includesOperator, Boltzmann collision operator]
  • A. involvesOperator chosen
    Indicates that a given process, action, or relationship includes or makes use of a specific operator as a participating element.
  • B. includesClause
    Indicates that one entity (typically a document, contract, or statement) contains or incorporates a specific clause as part of its content.
  • C. includedWith
    Indicates that one entity is provided or packaged together as part of another entity.
  • D. includes
    Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
  • E. otherOperator
    Indicates a relationship where one operator is distinguished from, or serves as an alternative to, another operator within the same context or system.
  • F. None of above.

Provenance (6 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb59182081908470f9be97e272c8 completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51a0e8ac8190992588bf2bf496ab completed March 9, 2026, 4:50 a.m.
NEDg Description generation batch_69ae521c7810819086b88bb5f062597e completed March 9, 2026, 4:52 a.m.
NED2 Entity disambiguation (via description) batch_69ae52e79c788190bbe6eb5baba08a71 completed March 9, 2026, 4:56 a.m.
PD Predicate disambiguation batch_69abb7bd86cc8190938ef06c1ed6d969 completed March 7, 2026, 5:29 a.m.
Created at: March 4, 2026, 7:44 p.m.