Triple
T7188613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kelvin |
E167630
|
entity |
| Predicate | BoltzmannConstantExactValue |
P75631
|
FINISHED |
| Object | 1.380649×10⁻²³ J⋅K⁻¹ |
—
|
LITERAL FINISHED |
How this triple was built (2 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: 1.380649×10⁻²³ J⋅K⁻¹ | Statement: [kelvin, BoltzmannConstantExactValue, 1.380649×10⁻²³ J⋅K⁻¹]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BoltzmannConstantExactValue Context triple: [kelvin, BoltzmannConstantExactValue, 1.380649×10⁻²³ J⋅K⁻¹]
-
A.
symbolOfStefanBoltzmannConstant
Indicates that something is the symbolic representation used to denote the Stefan–Boltzmann constant.
-
B.
energyPerDegreeOfFreedom
Indicates the amount of energy associated with each independent degree of freedom in a physical system.
-
C.
hasStefanBoltzmannConstantNamedAfter
Indicates that a physical constant is named after Stefan Boltzmann.
-
D.
naturalUnitsValue
Indicates that a quantity is expressed in natural units, specifying its value when fundamental physical constants are normalized (e.g., c = ħ = k_B = 1).
-
E.
CODATA2018RelativeStandardUncertainty
Indicates the relative standard uncertainty associated with a quantity as defined in the CODATA 2018 recommended values of fundamental physical constants.
- F. None of above. chosen
Provenance (4 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8e3d9188190ba2792098d76fb86 |
completed | March 27, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69c6e8b5f6508190af28e06a7959d717 |
completed | March 27, 2026, 8:29 p.m. |
Created at: March 27, 2026, 2:50 p.m.