Triple
T26421967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katzman Automatic Imaging Telescope |
E664262
|
entity |
| Predicate | hasImagingDetector |
P18614
|
FINISHED |
| Object | CCD camera |
—
|
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: CCD camera | Statement: [Katzman Automatic Imaging Telescope, hasImagingDetector, CCD camera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImagingDetector Context triple: [Katzman Automatic Imaging Telescope, hasImagingDetector, CCD camera]
-
A.
hasImagingType
Indicates the specific imaging modality or technique associated with or used in a given imaging procedure or result.
-
B.
imagingInstrument
Indicates that a particular instrument or device is used to capture or produce an image of a target or subject.
-
C.
hasFarDetector
Indicates that an entity is equipped with or associated with a detector positioned at a relatively large distance from a reference point or source.
-
D.
hasImagingCadence
Indicates the regular interval or frequency at which imaging observations are repeatedly acquired.
-
E.
hasCamera
chosen
Indicates that an entity is equipped with or possesses a camera.
- 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_69ee883a04ec81908883c4559f8c7e24 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 26, 2026, 11:43 p.m.