Triple
T3918660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landsat satellites |
E88905
|
entity |
| Predicate | hasSpatialResolutionRange |
P25684
|
FINISHED |
| Object | 15–120 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: 15–120 meters | Statement: [Landsat satellites, hasSpatialResolutionRange, 15–120 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpatialResolutionRange Context triple: [Landsat satellites, hasSpatialResolutionRange, 15–120 meters]
-
A.
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.
-
B.
spectralResolution
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
C.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
-
D.
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.
-
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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.