Triple
T20342141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shallow Radar |
E495764
|
entity |
| Predicate | verticalResolution |
P40836
|
FINISHED |
| Object | ~15 m in free space |
—
|
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: ~15 m in free space | Statement: [Shallow Radar, verticalResolution, ~15 m in free space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: verticalResolution Context triple: [Shallow Radar, verticalResolution, ~15 m in free space]
-
A.
displayResolution
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
B.
typicalResolution
Indicates the usual or standard level of detail or clarity at which something (such as an image, display, or representation) is normally rendered or presented.
-
C.
sensorResolution
chosen
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
D.
printingResolution
Indicates the level of detail or clarity at which something is printed, typically measured as resolution (e.g., dots per inch).
-
E.
viewfinderResolution
Indicates the resolution or level of detail provided by a device’s viewfinder display.
- 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_69e0b4a3320881909495ae8bc30bc2dc |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67835f6e881908834dda06cf66c50 |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:24 a.m.