Triple
T10921152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Five Cays |
E257948
|
entity |
| Predicate | hasNearbyEconomicSector |
P71206
|
FINISHED |
| Object | tourism on Providenciales |
—
|
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: tourism on Providenciales | Statement: [Five Cays, hasNearbyEconomicSector, tourism on Providenciales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyEconomicSector Context triple: [Five Cays, hasNearbyEconomicSector, tourism on Providenciales]
-
A.
hasNearbyIndustry
Indicates that an entity is located close to one or more industrial facilities or activities.
-
B.
hasNearbyEconomicRegion
Indicates that one economic region is geographically close to or adjacent to another economic region.
-
C.
nearbyEconomicActivity
chosen
Indicates that there is economic activity occurring in close physical proximity to the referenced entity.
-
D.
hasMajorCompanyNearby
Indicates that a location or entity is situated close to at least one large or significant company.
-
E.
associatedWithEconomicSector
Indicates that an entity has a connection or involvement with a particular economic sector, such as operating, participating, or being relevant within that sector.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77082a1488190850a4409339c3e1e |
completed | April 9, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69d72e799f808190b6ab64fc7586a303 |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:22 p.m.