Triple
T708257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magellan I |
E14148
|
entity |
| Predicate | apertureClass |
P2522
|
FINISHED |
| Object | 6–7 metre class 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: 6–7 metre class telescope | Statement: [Magellan I, apertureClass, 6–7 metre class telescope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: apertureClass Context triple: [Magellan I, apertureClass, 6–7 metre class telescope]
-
A.
hasApertureClass
chosen
Indicates that one entity is classified according to a specific aperture category or class of another entity.
-
B.
hasAperture
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
-
C.
exposureType
Indicates the specific manner or context in which one entity is exposed to another entity, condition, or influence.
-
D.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
E.
hasAIPhotoFeatures
Indicates that an entity provides or supports photo-related features powered by artificial intelligence.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5c011948190b2cfccd8fe722742 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f0217081908268b3f47e72f8df |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.