Triple
T8364028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playa Tortuga |
E197077
|
entity |
| Predicate | hasTourismStyle |
P82318
|
FINISHED |
| Object | low-impact 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: low-impact tourism | Statement: [Playa Tortuga, hasTourismStyle, low-impact tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTourismStyle Context triple: [Playa Tortuga, hasTourismStyle, low-impact tourism]
-
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.
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.
-
D.
containsTouristArea
Indicates that a place or region includes within its boundaries an area primarily designated or recognized for tourism activities.
-
E.
hasTouristInfrastructure
Indicates that a place is equipped with facilities and services designed to support and accommodate tourists.
- 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_69ca82f2dbe48190aba982e75a0d94de |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb808a67f88190849152102bfeb574 |
completed | March 31, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69cb70cd04b08190ab5f72afd22a7967 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d823b08190a54fadb50660cda5 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 6 p.m.