Triple
T19260933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horologium |
E481646
|
entity |
| Predicate | areaInSquareDegrees |
P20375
|
FINISHED |
| Object | about 249 |
—
|
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: about 249 | Statement: [Horologium, areaInSquareDegrees, about 249]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaInSquareDegrees Context triple: [Horologium, areaInSquareDegrees, about 249]
-
A.
areaSquareDegrees
chosen
Indicates the extent of a region or object measured as an area on the sky in square degrees.
-
B.
effectiveArea
Indicates the portion of a surface or region that actually contributes to a specified effect, such as performance, interaction, or impact, within a given context.
-
C.
angularSize
Indicates the apparent size of an object as seen from a given point, typically measured as the angle it subtends at the observer.
-
D.
minorAxisAngularSize_arcmin
Indicates the apparent angular size, measured in arcminutes, of the minor axis of an object as seen on the sky.
-
E.
surfaceBrightness_V_mag_per_arcsec2
Indicates the surface brightness of an object measured in V-band magnitudes per square arcsecond, relating its emitted light to the area it covers on the sky.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb890e7c8190beba407f63459382 |
completed | April 20, 2026, 10:10 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:28 p.m.