Triple
T10310162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Quintín |
E241865
|
entity |
| Predicate | tourismDevelopmentStatus |
P70107
|
FINISHED |
| Object | growing tourism destination |
—
|
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: growing tourism destination | Statement: [San Quintín, tourismDevelopmentStatus, growing tourism destination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismDevelopmentStatus Context triple: [San Quintín, tourismDevelopmentStatus, growing tourism destination]
-
A.
tourismDevelopmentLevel
chosen
Indicates the extent or intensity to which tourism-related infrastructure, services, and activities have been developed in a given area.
-
B.
tourismRegulation
Indicates that an authority establishes or enforces rules, policies, or controls governing tourism activities or the tourism sector.
-
C.
tourismTrend
Indicates how patterns or levels of tourism activity change over time or across locations.
-
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.
developedAsTouristAttractionBy
Indicates that an entity was created, enhanced, or promoted as a tourist attraction by a specific agent or organization.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:47 a.m.