Triple

T6455162
Position Surface form Disambiguated ID Type / Status
Subject William C. Reynolds E139974 entity
Predicate notableWork P4 FINISHED
Object Reynolds-averaged Navier–Stokes turbulence modeling
Reynolds-averaged Navier–Stokes turbulence modeling is a widely used computational fluid dynamics approach that predicts turbulent flows by averaging the Navier–Stokes equations and modeling the effects of turbulence through closure models.
E594627 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: Reynolds-averaged Navier–Stokes turbulence modeling | Statement: [William C. Reynolds, notableWork, Reynolds-averaged Navier–Stokes turbulence modeling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reynolds-averaged Navier–Stokes turbulence modeling
Context triple: [William C. Reynolds, notableWork, Reynolds-averaged Navier–Stokes turbulence modeling]
  • A. The Structure of Turbulent Shear Flow
    The Structure of Turbulent Shear Flow is a foundational scholarly work in fluid mechanics that analyzes the behavior, organization, and modeling of turbulence in shear flows.
  • B. Turbulent Flows
    Turbulent Flows is a comprehensive graduate-level textbook that rigorously presents the theory, modeling, and simulation of turbulent fluid motion in engineering and physics.
  • C. Kraichnan model of passive scalar advection
    The Kraichnan model of passive scalar advection is a theoretical framework in turbulence that studies how a passively transported quantity (like temperature or pollutant concentration) evolves in a fluid flow modeled by a Gaussian, white-in-time random velocity field.
  • D. The Theory of Homogeneous Turbulence
    The Theory of Homogeneous Turbulence is a classic monograph in fluid dynamics that provides a rigorous mathematical treatment of statistically uniform turbulent flows.
  • E. A First Course in Turbulence
    A First Course in Turbulence is a foundational textbook that introduces the theory, physics, and mathematical modeling of turbulent flows for advanced students in fluid mechanics.
  • 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: Reynolds-averaged Navier–Stokes turbulence modeling
Triple: [William C. Reynolds, notableWork, Reynolds-averaged Navier–Stokes turbulence modeling]
Generated description
Reynolds-averaged Navier–Stokes turbulence modeling is a widely used computational fluid dynamics approach that predicts turbulent flows by averaging the Navier–Stokes equations and modeling the effects of turbulence through closure models.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Reynolds-averaged Navier–Stokes turbulence modeling
Target entity description: Reynolds-averaged Navier–Stokes turbulence modeling is a widely used computational fluid dynamics approach that predicts turbulent flows by averaging the Navier–Stokes equations and modeling the effects of turbulence through closure models.
  • A. The Structure of Turbulent Shear Flow
    The Structure of Turbulent Shear Flow is a foundational scholarly work in fluid mechanics that analyzes the behavior, organization, and modeling of turbulence in shear flows.
  • B. Turbulent Flows
    Turbulent Flows is a comprehensive graduate-level textbook that rigorously presents the theory, modeling, and simulation of turbulent fluid motion in engineering and physics.
  • C. Kraichnan model of passive scalar advection
    The Kraichnan model of passive scalar advection is a theoretical framework in turbulence that studies how a passively transported quantity (like temperature or pollutant concentration) evolves in a fluid flow modeled by a Gaussian, white-in-time random velocity field.
  • D. The Theory of Homogeneous Turbulence
    The Theory of Homogeneous Turbulence is a classic monograph in fluid dynamics that provides a rigorous mathematical treatment of statistically uniform turbulent flows.
  • E. A First Course in Turbulence
    A First Course in Turbulence is a foundational textbook that introduces the theory, physics, and mathematical modeling of turbulent flows for advanced students in fluid mechanics.
  • 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_69c008b301948190a35854e5284dc822 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c069d339788190992e3299ffe30d58 completed March 22, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bd982208190bbf5f00a85f7098d completed March 27, 2026, 9:20 a.m.
NEDg Description generation batch_69c64d8fe71881908417dc1d3f242bd5 completed March 27, 2026, 9:27 a.m.
NED2 Entity disambiguation (via description) batch_69c64e5cd1b88190abcdc8af02991d1d completed March 27, 2026, 9:31 a.m.
Created at: March 22, 2026, 4:48 p.m.