Triple
T4741740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boa Vista (Cape Verde) |
E105258
|
entity |
| Predicate | tourismDevelopment |
P45842
|
FINISHED |
| Object | rapid growth since late 20th century |
—
|
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: rapid growth since late 20th century | Statement: [Boa Vista (Cape Verde), tourismDevelopment, rapid growth since late 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismDevelopment Context triple: [Boa Vista (Cape Verde), tourismDevelopment, rapid growth since late 20th century]
-
A.
tourismBoom
chosen
Indicates a rapid and significant increase in tourism activity, such as visitor numbers, spending, or development, within a particular place or period.
-
B.
tourismTheme
Indicates the main subject or focus of a tourism-related activity, service, or destination (such as cultural, adventure, or eco-tourism).
-
C.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
D.
tourismImportance
Indicates the degree to which a place or entity is significant or valuable as a destination or attraction for tourists.
-
E.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another location.
- 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.