Triple
T4741741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boa Vista (Cape Verde) |
E105258
|
entity |
| Predicate | primaryTouristMarket |
P34539
|
FINISHED |
| Object | European tourists |
—
|
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: European tourists | Statement: [Boa Vista (Cape Verde), primaryTouristMarket, European tourists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTouristMarket Context triple: [Boa Vista (Cape Verde), primaryTouristMarket, European tourists]
-
A.
primaryTourismHub
Indicates that a location serves as the main center or focal point for tourism activities within a given area or region.
-
B.
primaryVisitors
chosen
Indicates that certain entities are the main or most important visitors associated with another entity or context.
-
C.
tourismBoom
Indicates a rapid and significant increase in tourism activity, such as visitor numbers, spending, or development, within a particular place or period.
-
D.
primaryTarget
Indicates that an entity is the main or most important target of another entity’s action, focus, or effect.
-
E.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
- 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_69bd43ef87a48190a5bc3600711aa032 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64a7153881909eac451fc7566d25 |
completed | March 20, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69bd6221c3b881908604f35f8de6f16b |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:19 p.m.