Triple
T12791969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern African Large Telescope |
E305787
|
entity |
| Predicate | mirrorSegments |
P8981
|
FINISHED |
| Object | 91 |
—
|
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: 91 | Statement: [Southern African Large Telescope, mirrorSegments, 91]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mirrorSegments Context triple: [Southern African Large Telescope, mirrorSegments, 91]
-
A.
mirrorType
Indicates that one entity is a specific kind or category of mirror in relation to another entity.
-
B.
mirrorCount
chosen
Indicates the number of mirrors associated with or present in relation to a given entity or context.
-
C.
mirrorTechnology
Indicates a relationship where one technology closely reflects, imitates, or duplicates the functionality or design of another.
-
D.
mirroredAt
Indicates that one entity is a mirror image or reflection of another entity with respect to a specified axis, plane, or point.
-
E.
secondaryMirrorShape
Indicates that one entity specifies or defines the geometric shape of a secondary mirror associated with another entity.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e6b55248190ab938e69eb263612 |
completed | April 10, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:30 p.m.