Triple
T8111594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kueyen |
E189365
|
entity |
| Predicate | hasMirrorCount |
P8981
|
FINISHED |
| Object | 1 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: 1 primary mirror | Statement: [Kueyen, hasMirrorCount, 1 primary mirror]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMirrorCount Context triple: [Kueyen, hasMirrorCount, 1 primary mirror]
-
A.
mirrorCount
chosen
Indicates the number of mirrors associated with or present in relation to a given entity or context.
-
B.
hasMirrorSupportSystem
Indicates that an entity is equipped with or connected to a system that supports or stabilizes a mirror.
-
C.
hasSecondaryMirrorPosition
Indicates the spatial placement or configuration of a secondary mirror relative to the primary optical system.
-
D.
mirrorType
Indicates that one entity is a specific kind or category of mirror in relation to another entity.
-
E.
numberOfPrimaryMirrorSegments
Indicates the total count of individual segments that make up 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4664fef881908b0dc7b158aca398 |
completed | March 31, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69cb368e7f4c81909aabd7716f0de79d |
completed | March 31, 2026, 2:50 a.m. |
Created at: March 30, 2026, 5:32 p.m.