Triple

T7051675
Position Surface form Disambiguated ID Type / Status
Subject G. I. Taylor E163980 entity
Predicate knownFor P22 FINISHED
Object Taylor microscale in turbulence
The Taylor microscale in turbulence is a characteristic length scale that quantifies the size of eddies where viscous dissipation begins to significantly affect turbulent motion, bridging the gap between large energy-containing eddies and the smallest dissipative scales.
E638889 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: Taylor microscale in turbulence | Statement: [G. I. Taylor, knownFor, Taylor microscale in turbulence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taylor microscale in turbulence
Context triple: [G. I. Taylor, knownFor, Taylor microscale in turbulence]
  • 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. 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.
  • C. 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.
  • D. Kolmogorov spectrum of turbulence
    The Kolmogorov spectrum of turbulence is a fundamental theory in fluid dynamics that predicts how kinetic energy is distributed across different scales in fully developed turbulent flow, most famously yielding the −5/3 power law for the inertial subrange.
  • E. 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.
  • 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: Taylor microscale in turbulence
Triple: [G. I. Taylor, knownFor, Taylor microscale in turbulence]
Generated description
The Taylor microscale in turbulence is a characteristic length scale that quantifies the size of eddies where viscous dissipation begins to significantly affect turbulent motion, bridging the gap between large energy-containing eddies and the smallest dissipative scales.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Taylor microscale in turbulence
Target entity description: The Taylor microscale in turbulence is a characteristic length scale that quantifies the size of eddies where viscous dissipation begins to significantly affect turbulent motion, bridging the gap between large energy-containing eddies and the smallest dissipative scales.
  • 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. 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.
  • C. 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.
  • D. Kolmogorov spectrum of turbulence
    The Kolmogorov spectrum of turbulence is a fundamental theory in fluid dynamics that predicts how kinetic energy is distributed across different scales in fully developed turbulent flow, most famously yielding the −5/3 power law for the inertial subrange.
  • E. 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.
  • 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_69c68861678881909961ddf4d779f750 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e2500570819087200013d859cfe6 completed March 27, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c78891bc5081909db384a35b45df4a completed March 28, 2026, 7:51 a.m.
NEDg Description generation batch_69c7893f85588190b1ed983f00ea2532 completed March 28, 2026, 7:54 a.m.
NED2 Entity disambiguation (via description) batch_69c78b0fe83481909cad77ce740b81d5 completed March 28, 2026, 8:02 a.m.
Created at: March 27, 2026, 2:37 p.m.