Triple
T806519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassegrain focus |
E17448
|
entity |
| Predicate | usesSecondaryMirror |
P8983
|
FINISHED |
| Object | convex secondary 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: convex secondary mirror | Statement: [Cassegrain focus, usesSecondaryMirror, convex secondary mirror]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSecondaryMirror Context triple: [Cassegrain focus, usesSecondaryMirror, convex secondary mirror]
-
A.
hasSecondaryMirrorPosition
Indicates the spatial placement or configuration of a secondary mirror relative to the primary optical system.
-
B.
secondaryMirrorShape
chosen
Indicates that one entity specifies or defines the geometric shape of a secondary mirror associated with another entity.
-
C.
primaryMirrorShape
Indicates that one entity has a primary mirror whose geometric shape or curvature type is specified by the other entity.
-
D.
mirrorType
Indicates that one entity is a specific kind or category of mirror in relation to another entity.
-
E.
primaryMirrorConfiguration
Indicates the specific structural and optical setup used for a system’s primary mirror.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ac07fedc8190ab05595f25c1792f |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7221c081908068e66fe720f26d |
completed | March 1, 2026, 9:06 p.m. |
Created at: March 1, 2026, 7:38 p.m.