Triple
T1406371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Bank Observatory |
E31700
|
entity |
| Predicate | hasApertureSize |
P12152
|
FINISHED |
| Object | 100 meters (Green Bank 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: 100 meters (Green Bank Telescope) | Statement: [Green Bank Observatory, hasApertureSize, 100 meters (Green Bank Telescope)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApertureSize Context triple: [Green Bank Observatory, hasApertureSize, 100 meters (Green Bank Telescope)]
-
A.
hasAperture
chosen
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
-
B.
hasApertureClass
Indicates that one entity is classified according to a specific aperture category or class of another entity.
-
C.
hasFocalRatioRange
Indicates that an entity is associated with a range of possible focal ratios, specifying the minimum and maximum f-number values it can have.
-
D.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
E.
telephotoOpticalZoom
Indicates that the relationship involves zooming in optically with a telephoto lens to magnify a subject without digital enlargement.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3be10348190ade8a73780d2c008 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf030a388190bc82d30b9233e873 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.