Triple
T9838066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SPOT Earth observation satellites |
E239151
|
entity |
| Predicate | regionOfCoverage |
P19200
|
FINISHED |
| Object | global |
—
|
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: global | Statement: [SPOT Earth observation satellites, regionOfCoverage, global]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOfCoverage Context triple: [SPOT Earth observation satellites, regionOfCoverage, global]
-
A.
regionCoverage
chosen
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
-
B.
providesCoverage
Indicates that one entity supplies protection, insurance, or service coverage to another entity or for a specified risk or scope.
-
C.
serviceCovered
Indicates that a particular service is included within the scope, benefits, or obligations defined by a given plan, agreement, or coverage.
-
D.
typeOfCoverage
Indicates the specific kind or category of coverage that applies in a given context (such as insurance, service, or protection).
-
E.
dataCoverage
Indicates the extent or proportion of relevant data that is included, captured, or represented within a given dataset or system.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb347ff4c81908c312548a25bae71 |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:33 p.m.