Triple
T32386592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazonia-1 |
E827558
|
entity |
| Predicate | groundResolution |
P25684
|
FINISHED |
| Object | approximately 60 meters |
—
|
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: approximately 60 meters | Statement: [Amazonia-1, groundResolution, approximately 60 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: groundResolution Context triple: [Amazonia-1, groundResolution, approximately 60 meters]
-
A.
mapScale
Indicates the ratio between distances on a map and the corresponding actual distances in the real world.
-
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.
elevationAccuracy
Indicates the degree of precision or reliability associated with a measured or reported elevation value in the relationship.
-
D.
depthApproxKm
Indicates the approximate depth of something measured in kilometers.
-
E.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
- 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_69f349184e7481909c6c54428cb9cf12 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c1d26e608190abfa275a4c02a3ce |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:51 a.m.