Triple
T2683336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gibbons–Hawking temperature |
E57424
|
entity |
| Predicate | relatedFormula |
P12675
|
FINISHED |
| Object | T = \frac{\hbar}{2\pi k_B} \sqrt{\frac{\Lambda}{3}} |
—
|
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: T = \frac{\hbar}{2\pi k_B} \sqrt{\frac{\Lambda}{3}} | Statement: [Gibbons–Hawking temperature, relatedFormula, T = \frac{\hbar}{2\pi k_B} \sqrt{\frac{\Lambda}{3}}]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedFormula
Context triple: [Gibbons–Hawking temperature, relatedFormula, T = \frac{\hbar}{2\pi k_B} \sqrt{\frac{\Lambda}{3}}]
-
A.
relatedByFormula
Indicates that one entity is mathematically or logically derived from, or connected to, another according to a specific formula.
-
B.
formulaUsed
Indicates that a particular formula is employed or applied in performing a calculation, derivation, or reasoning step.
-
C.
keyFormula
Indicates that a formula serves as the primary or defining expression associated with an entity or relationship.
-
D.
mathematicallyExpressedBy
chosen
Indicates that something (such as a concept, quantity, or relationship) is represented or captured using a specific mathematical expression or formulation.
-
E.
relatedForm
Indicates that one entity is an alternative or variant form of another, such as a different spelling, inflection, or closely related lexical form.
- F. None of above.
Provenance (3 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9d7692c81909d8fd9ce3817161b |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd81c9b4c81908e5e0da6ac5f828b |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.