Triple
T31795765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tweed Caldera |
E811592
|
entity |
| Predicate | hasDiameterInKilometers |
P38869
|
FINISHED |
| Object | 40 |
—
|
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: 40 | Statement: [Tweed Caldera, hasDiameterInKilometers, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiameterInKilometers Context triple: [Tweed Caldera, hasDiameterInKilometers, 40]
-
A.
hasPolarDiameter_km
Indicates the length of an object's diameter measured from pole to pole, expressed in kilometers.
-
B.
meanDiameter_km
chosen
Indicates the average diameter of an object or region measured in kilometers.
-
C.
hasEquatorialDiameter_km
Indicates the measurement, in kilometers, of an object's diameter across its equator.
-
D.
hasMeanRadius
Indicates that an entity possesses a specified average radius measurement, typically representing the mean distance from its center to its surface.
-
E.
averageDiameter
Indicates the mean value of the diameters of a set of objects or instances in the relationship.
- 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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe38be079c8190a240191ac0e73e3a |
completed | May 8, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69fe350344508190930de2218156ca02 |
completed | May 8, 2026, 7:09 p.m. |
Created at: April 30, 2026, 11:40 p.m.