Triple
T21123515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landsat 8 |
E520491
|
entity |
| Predicate | imageResolutionThermal |
P142931
|
FINISHED |
| Object | 100 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: 100 meters | Statement: [Landsat 8, imageResolutionThermal, 100 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageResolutionThermal Context triple: [Landsat 8, imageResolutionThermal, 100 meters]
-
A.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
B.
telephotoCameraResolution
Indicates the image resolution capability of a device’s telephoto camera in a given context.
-
C.
imageQuality
Indicates the assessed level or degree of visual clarity, detail, and overall fidelity of an image.
-
D.
hasCameraResolution
Indicates that an entity is associated with a specific camera resolution value or specification.
-
E.
viewfinderResolution
Indicates the resolution or level of detail provided by a device’s viewfinder display.
- F. None of above. chosen
Provenance (4 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_69e0b50a623881909c0bbaf4f2c055e7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72236b2d88190bef9f0cd6924ca92 |
completed | April 21, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69e5f5ed6c8c8190b31092a5d4c3de5d |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f993240c8190847c0b08e65726c8 |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 2:55 p.m.