Triple
T32141787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burkert profile |
E820923
|
entity |
| Predicate | dimensionlessRadius |
P108234
|
FINISHED |
| Object | x = r/r₀ |
—
|
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: x = r/r₀ | Statement: [Burkert profile, dimensionlessRadius, x = r/r₀]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionlessRadius Context triple: [Burkert profile, dimensionlessRadius, x = r/r₀]
-
A.
dimensionlessForm
Indicates that one quantity is expressed in a normalized, unitless form relative to a reference scale or value.
-
B.
radiusRatio
chosen
Indicates the proportional relationship between one radius and another, typically expressing how large one is relative to the other.
-
C.
hasMeanRadius
Indicates that an entity possesses a specified average radius measurement, typically representing the mean distance from its center to its surface.
-
D.
円の直径比率
Indicates the proportional relationship between a circle’s diameter and another referenced measure (such as another diameter or a standard length).
-
E.
ringRadius
Indicates the size of a ring by specifying the distance from its center to its outer edge.
- 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_69f3490520d081909b2f1271dab75faa |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b9aed8c881908214b59cb895fa65 |
completed | May 3, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a970b0819090c6473844ffa8e3 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:30 a.m.