Triple
T490650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant Magellan Telescope |
E9980
|
entity |
| Predicate | effectiveApertureDiameter |
P2517
|
FINISHED |
| Object | ~24.5 meters |
—
|
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: ~24.5 meters | Statement: [Giant Magellan Telescope, effectiveApertureDiameter, ~24.5 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectiveApertureDiameter Context triple: [Giant Magellan Telescope, effectiveApertureDiameter, ~24.5 meters]
-
A.
twinTelescopeAperture
Indicates that two telescopes share the same aperture size or have apertures that are functionally equivalent.
-
B.
primaryMirrorDiameter
chosen
Indicates the diameter of the primary mirror used in an optical system or instrument.
-
C.
highGainAntennaDiameter
Indicates the physical diameter measurement of a high-gain antenna associated with an entity.
-
D.
hasAperture
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
-
E.
angularSize
Indicates the apparent size of an object as seen from a given point, typically measured as the angle it subtends at the observer.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0e22a308190b04d12974fd08a38 |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf7ce008190836fb6ab5ea39375 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.