Triple
T17661797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PFS |
E440269
|
entity |
| Predicate | primaryMirrorDiameterOfHostTelescope |
P2517
|
FINISHED |
| Object | 8.2 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: 8.2 meters | Statement: [PFS, primaryMirrorDiameterOfHostTelescope, 8.2 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryMirrorDiameterOfHostTelescope Context triple: [PFS, primaryMirrorDiameterOfHostTelescope, 8.2 meters]
-
A.
primaryMirrorDiameter
chosen
Indicates the diameter of the primary mirror used in an optical system or instrument.
-
B.
secondaryMirrorDiameter
Indicates the diameter measurement of a system’s secondary mirror in a multi-mirror optical setup.
-
C.
auxiliaryTelescopeAperture
Indicates that one entity functions as the auxiliary telescope whose aperture (opening/diameter) is being specified or associated with another entity.
-
D.
largestTelescopeAperture
Indicates that one entity has the largest telescope aperture (e.g., diameter or area of the primary light-collecting element) among a specified set or context.
-
E.
radioTelescopeDiameter
Indicates the size of a radio telescope as measured by the diameter of its main collecting dish or antenna.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea67f8081909da164ca21a98675 |
completed | April 19, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 9:43 a.m.