Triple
T14245979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bouma National Heritage Park |
E353133
|
entity |
| Predicate | tourismModel |
P113375
|
FINISHED |
| Object | community-based ecotourism |
—
|
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: community-based ecotourism | Statement: [Bouma National Heritage Park, tourismModel, community-based ecotourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismModel Context triple: [Bouma National Heritage Park, tourismModel, community-based ecotourism]
-
A.
tourismTheme
Indicates the main subject or focus of a tourism-related activity, service, or destination (such as cultural, adventure, or eco-tourism).
-
B.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
C.
tourismTrend
Indicates how patterns or levels of tourism activity change over time or across locations.
-
D.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
E.
tourismBoom
Indicates a rapid and significant increase in tourism activity, such as visitor numbers, spending, or development, within a particular place or period.
- F. None of above. chosen
Provenance (4 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de629464f88190817b190731bab156 |
completed | April 14, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69de05c09b7881908acbca18bd7d997c |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239bd0f48190ada38c0261e0ef3c |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 1:08 a.m.