Triple
T6917155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Botswana and Zimbabwe |
E160088
|
entity |
| Predicate | shareTourismAssets |
P55845
|
FINISHED |
| Object | wildlife-based tourism |
—
|
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: wildlife-based tourism | Statement: [Botswana and Zimbabwe, shareTourismAssets, wildlife-based tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareTourismAssets Context triple: [Botswana and Zimbabwe, shareTourismAssets, wildlife-based tourism]
-
A.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
B.
hasTourismResource
chosen
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
-
C.
tourismDraw
Indicates that one entity attracts tourists or visitor interest to another entity or location.
-
D.
tourismBoom
Indicates a rapid and significant increase in tourism activity, such as visitor numbers, spending, or development, within a particular place or period.
-
E.
tourismMarket
Indicates a relationship where a location, service, or product functions as a destination or offering within the travel and tourism economy, attracting and serving tourists as a market segment.
- 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_69c6883ab1008190a07129ff06f625d9 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9e034cc81908f1e8f31b055e119 |
completed | March 27, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:26 p.m.