Triple
T607235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerro Tololo Inter-American Observatory |
E12020
|
entity |
| Predicate | hasMirrorDiameter |
P2517
|
FINISHED |
| Object | 4 meters for Víctor M. Blanco Telescope |
—
|
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: 4 meters for Víctor M. Blanco Telescope | Statement: [Cerro Tololo Inter-American Observatory, hasMirrorDiameter, 4 meters for Víctor M. Blanco Telescope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMirrorDiameter Context triple: [Cerro Tololo Inter-American Observatory, hasMirrorDiameter, 4 meters for Víctor M. Blanco Telescope]
-
A.
primaryMirrorDiameter
chosen
Indicates the diameter of the primary mirror used in an optical system or instrument.
-
B.
primaryMirrorShape
Indicates that one entity has a primary mirror whose geometric shape or curvature type is specified by the other entity.
-
C.
hasSecondaryMirrorPosition
Indicates the spatial placement or configuration of a secondary mirror relative to the primary optical system.
-
D.
secondaryMirrorShape
Indicates that one entity specifies or defines the geometric shape of a secondary mirror associated with another entity.
-
E.
mirrorCount
Indicates the number of mirrors associated with or present in relation to a given entity or context.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df34abc8190a578c8c2ab3d28e4 |
completed | March 1, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69a49cf8fc1c81908a9c7df552aa1a59 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.