Triple
T16690854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HRSC |
E405588
|
entity |
| Predicate | maximumGroundResolution |
P25684
|
FINISHED |
| Object | about 10 m per pixel |
—
|
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: about 10 m per pixel | Statement: [HRSC, maximumGroundResolution, about 10 m per pixel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumGroundResolution Context triple: [HRSC, maximumGroundResolution, about 10 m per pixel]
-
A.
maximumResolution
Indicates the highest level of detail or fineness at which something (such as an image, display, or measurement) can be represented or processed.
-
B.
hasSpatialResolution
chosen
Indicates that something is characterized by a specific level of spatial detail or granularity at which it can represent or distinguish features in space.
-
C.
maximumExtent
Indicates the greatest or furthest degree, size, or range to which something can extend or apply within a given context.
-
D.
maximumGradient
Indicates the greatest rate of change or steepest slope that occurs within a given function, surface, or dataset.
-
E.
mainResolution
Indicates that one resolution is the primary or most important resolution associated with a given context or entity.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ea8cabc8190ba321503399960da |
completed | April 18, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:19 a.m.