Triple
T19269234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassegrain telescope design |
E481876
|
entity |
| Predicate | hasFocalPlaneLocation |
P21256
|
FINISHED |
| Object | behind primary mirror |
—
|
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: behind primary mirror | Statement: [Cassegrain telescope design, hasFocalPlaneLocation, behind primary mirror]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFocalPlaneLocation Context triple: [Cassegrain telescope design, hasFocalPlaneLocation, behind primary mirror]
-
A.
hasFocalPlane
chosen
Indicates that an optical system or imaging device possesses a specific focal plane where light is brought into focus.
-
B.
hasFocalPlaneArea
Indicates that an entity has a specific area measurement associated with its focal plane.
-
C.
focalPlaneHeight
Indicates the vertical distance or elevation of the focal plane relative to a defined reference level or surface.
-
D.
hasFocalPoint
Indicates that something possesses a central point of focus or primary area of attention within its structure, composition, or activity.
-
E.
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.
- 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_69e5fbb68d0c819083ba0ce680dd7d99 |
completed | April 20, 2026, 10:11 a.m. |
| PD | Predicate disambiguation | batch_69e4dd07a7208190afcd51ba1dc87c33 |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:29 p.m.