Triple
T10266527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Look Around |
E240724
|
entity |
| Predicate | imageryCoverage |
P1987
|
FINISHED |
| Object | selected cities and regions worldwide |
—
|
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: selected cities and regions worldwide | Statement: [Look Around, imageryCoverage, selected cities and regions worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageryCoverage Context triple: [Look Around, imageryCoverage, selected cities and regions worldwide]
-
A.
mapCoverage
chosen
Indicates the extent or area that is represented, covered, or included by a particular map.
-
B.
regionCoverage
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
-
C.
digitalCoverage
Indicates that one entity provides or has access to digital services, connectivity, or online resources for another entity or within a specified area.
-
D.
hemisphereCoverageByImaging
Indicates the extent to which a particular hemisphere is covered or captured by an imaging procedure or dataset.
-
E.
hasColorImagery
Indicates that something includes or is characterized by visual elements emphasizing specific colors or color-based symbolism.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2872830819080fdfa816167d04c |
completed | April 7, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ef6e6c81908a8ee52e4d28127b |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:34 a.m.