Triple
T11109337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simonyi Survey Telescope |
E262713
|
entity |
| Predicate | secondaryMirrorDiameter |
P97315
|
FINISHED |
| Object | 3.4 m |
—
|
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: 3.4 m | Statement: [Simonyi Survey Telescope, secondaryMirrorDiameter, 3.4 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryMirrorDiameter Context triple: [Simonyi Survey Telescope, secondaryMirrorDiameter, 3.4 m]
-
A.
primaryMirrorDiameter
Indicates the diameter of the primary mirror used in an optical system or instrument.
-
B.
secondaryMirrorShape
Indicates that one entity specifies or defines the geometric shape of a secondary mirror associated with another entity.
-
C.
hasSecondaryMirrorPosition
Indicates the spatial placement or configuration of a secondary mirror relative to the primary optical system.
-
D.
auxiliaryTelescopeAperture
Indicates that one entity functions as the auxiliary telescope whose aperture (opening/diameter) is being specified or associated with another entity.
-
E.
twinTelescopeAperture
Indicates that two telescopes share the same aperture size or have apertures that are functionally equivalent.
- F. None of above. chosen
Provenance (4 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a6896c0819082685b5b4600d158 |
completed | April 9, 2026, 12:24 p.m. |
| PD | Predicate disambiguation | batch_69d7441cf8188190b8095f622c923156 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750ca52ec8190a559432a5de106fd |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:27 p.m.