Triple
T4411115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W. M. Keck Observatory |
E94854
|
entity |
| Predicate | hasMirrorSegments |
P14317
|
FINISHED |
| Object | 36 (per 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: 36 (per primary mirror) | Statement: [W. M. Keck Observatory, hasMirrorSegments, 36 (per primary mirror)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMirrorSegments Context triple: [W. M. Keck Observatory, hasMirrorSegments, 36 (per primary mirror)]
-
A.
hasMirrorSupportSystem
Indicates that an entity is equipped with or connected to a system that supports or stabilizes a mirror.
-
B.
numberOfPrimaryMirrorSegments
chosen
Indicates the total count of individual segments that make up a system’s primary mirror.
-
C.
hasSecondaryMirrorPosition
Indicates the spatial placement or configuration of a secondary mirror relative to the primary optical system.
-
D.
hasMultipleSegments
Indicates that the referenced entity is composed of more than one distinct segment or section.
-
E.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
- 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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b354e4c58c8190b4190aad3095a1dd |
completed | March 13, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69b34f5b36a881909bf2e970aa523390 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:29 p.m.