Triple
T10452263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makili |
E246454
|
entity |
| Predicate | hasTourismPotential |
P94116
|
FINISHED |
| Object | marine 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: marine ecotourism | Statement: [Makili, hasTourismPotential, marine ecotourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTourismPotential Context triple: [Makili, hasTourismPotential, marine ecotourism]
-
A.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
B.
hasTourismResource
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
-
C.
hasTourismStyle
Indicates the type or style of tourism associated with or characteristic of a particular entity.
-
D.
hasTourismImpactOn
Indicates that one entity affects or influences the tourism levels, patterns, or attractiveness of another entity.
-
E.
hasTourismHub
Indicates that a place functions as a central location or focal point for tourism-related activities, services, or attractions for another place or region.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe0b7bb481908182c7b9a80af3b3 |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb7d353c8190a73f439a956c7606 |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d4fe058fcc81909428137d9ffd6d90 |
completed | April 7, 2026, 12:52 p.m. |
Created at: April 6, 2026, 12:17 p.m.