Triple
T2707270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeans mass |
E59371
|
entity |
| Predicate | approximateFormula |
P4460
|
FINISHED |
| Object | M_J ∝ T^{3/2} ρ^{-1/2} |
—
|
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: M_J ∝ T^{3/2} ρ^{-1/2} | Statement: [Jeans mass, approximateFormula, M_J ∝ T^{3/2} ρ^{-1/2}]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateFormula
Context triple: [Jeans mass, approximateFormula, M_J ∝ T^{3/2} ρ^{-1/2}]
-
A.
approximates
chosen
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
B.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
C.
formulaUsed
Indicates that a particular formula is employed or applied in performing a calculation, derivation, or reasoning step.
-
D.
mathematicallyExpressedBy
Indicates that something (such as a concept, quantity, or relationship) is represented or captured using a specific mathematical expression or formulation.
-
E.
recitesFormula
Indicates that one entity verbally or mentally repeats a specific formula, such as a set phrase, equation, or ritual wording, typically from memory.
- 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda725f24819090e8d936b3d2d5bc |
completed | March 7, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69abd8224c688190bb4a362360b03007 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.