Triple
T3918655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landsat satellites |
E88905
|
entity |
| Predicate | hasImagingType |
P52562
|
FINISHED |
| Object | multispectral imagery |
—
|
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: multispectral imagery | Statement: [Landsat satellites, hasImagingType, multispectral imagery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImagingType Context triple: [Landsat satellites, hasImagingType, multispectral imagery]
-
A.
imagedBy
Indicates that something is captured, recorded, or represented in an image created by a particular imaging device, method, or agent.
-
B.
hasAIPhotoFeatures
Indicates that an entity provides or supports photo-related features powered by artificial intelligence.
-
C.
hasAcquisitionType
Indicates the specific kind or category of acquisition relationship that exists between one entity acquiring another.
-
D.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
E.
imagedIn
Indicates that one entity appears within or is depicted in an image associated with another entity.
- 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_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. |
| PDg | Predicate description generation | batch_69aef18748648190b85e62f7796ff4b4 |
completed | March 9, 2026, 4:12 p.m. |
Created at: March 9, 2026, 3:22 p.m.