Triple
T24547037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Effelsberg 100-m Radio Telescope |
E607254
|
entity |
| Predicate | apertureType |
P2522
|
FINISHED |
| Object | single-dish |
—
|
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: single-dish | Statement: [Effelsberg 100-m Radio Telescope, apertureType, single-dish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: apertureType Context triple: [Effelsberg 100-m Radio Telescope, apertureType, single-dish]
-
A.
hasAperture
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
-
B.
hasApertureShape
Indicates that an entity’s aperture (opening) has a specific geometric or descriptive shape.
-
C.
hasApertureClass
chosen
Indicates that one entity is classified according to a specific aperture category or class of another entity.
-
D.
rearCameraAperture
Indicates the size or f-stop value of the aperture used by a device’s rear-facing camera when capturing images or video.
-
E.
cameraLensType
Indicates the specific type or category of lens used or associated with 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_69e2c4c9bf94819082d05da6f5c29907 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8caba8c819082c3bf33b6ff9cd0 |
completed | April 30, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.