Triple
T5201978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SagDEG |
E117412
|
entity |
| Predicate | hasAngularSize_approx |
P6952
|
FINISHED |
| Object | several tens of degrees along its major axis |
—
|
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: several tens of degrees along its major axis | Statement: [SagDEG, hasAngularSize_approx, several tens of degrees along its major axis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAngularSize_approx Context triple: [SagDEG, hasAngularSize_approx, several tens of degrees along its major axis]
-
A.
angularSize
chosen
Indicates the apparent size of an object as seen from a given point, typically measured as the angle it subtends at the observer.
-
B.
hasDimensionsApprox
Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
-
C.
approximateRadius
Indicates that one entity specifies or provides an estimated value for the radius of another entity.
-
D.
approximateDiameter
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
-
E.
hasMeanRadius
Indicates that an entity possesses a specified average radius measurement, typically representing the mean distance from its center to its surface.
- 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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7adb034c819086bf8a85fbf158f4 |
completed | March 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69bd77b9a67c8190819612257ea746b4 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:47 p.m.