Triple
T38479663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panchromatic Camera 2 |
E915635
|
entity |
| Predicate | observationDiscipline |
P155682
|
FINISHED |
| Object | remote sensing |
—
|
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: remote sensing | Statement: [Panchromatic Camera 2, observationDiscipline, remote sensing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: observationDiscipline Context triple: [Panchromatic Camera 2, observationDiscipline, remote sensing]
-
A.
observationPractice
chosen
Indicates a relationship where one entity engages in or applies a method, routine, or discipline of observing another entity or phenomenon.
-
B.
observationType
Indicates the specific kind or category of observation being made or recorded in a given context.
-
C.
observation
Indicates that one entity perceives, monitors, or takes note of another entity or phenomenon, typically to gather information about it.
-
D.
observationNote
Indicates that there is an associated free-text comment or remark providing additional details or context about an observation.
-
E.
observationBenefit
Indicates that one entity gains an advantage, insight, or positive outcome as a result of observing another entity or phenomenon.
- 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_69f76e8ff5cc8190a88803369183845e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcd313e61c8190b174b331365b803f |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f6b2e08190bf0300ae7c9ae67a |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:31 p.m.