Triple
T4637481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schmidt–Cassegrain telescope design |
E101567
|
entity |
| Predicate | canUseFocalReducer |
P57895
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Schmidt–Cassegrain telescope design, canUseFocalReducer, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canUseFocalReducer Context triple: [Schmidt–Cassegrain telescope design, canUseFocalReducer, true]
-
A.
hasFocalRatio
Indicates a relationship where an optical system is associated with a specific focal ratio (f-number) that characterizes its light-gathering speed and image brightness.
-
B.
hasFocalPlane
Indicates that an optical system or imaging device possesses a specific focal plane where light is brought into focus.
-
C.
hasFocalRatioRange
Indicates that an entity is associated with a range of possible focal ratios, specifying the minimum and maximum f-number values it can have.
-
D.
focalLengthExtensionMethod
Indicates a method or technique used to extend or modify the effective focal length in an optical or imaging system.
-
E.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a62a9e48190b0cf1cbcc51f00c0 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56f7b94481909f3335312becd446 |
completed | March 20, 2026, 2:17 p.m. |
Created at: March 20, 2026, 1:13 p.m.