Triple
T22464334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kulon Progo Regency |
E555310
|
entity |
| Predicate | hasGrowingTourismSector |
P148309
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kulon Progo Regency, hasGrowingTourismSector, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrowingTourismSector Context triple: [Kulon Progo Regency, hasGrowingTourismSector, true]
-
A.
hasTourismDevelopment
Indicates that tourism-related infrastructure, services, or activities have been developed or promoted in relation to the referenced entity.
-
B.
hasTourismIndustry
Indicates that a place or region possesses an established tourism industry, involving organized services and activities catering to visitors and travelers.
-
C.
hadTourismEconomyFor
Indicates that an entity has sustained a tourism-based economy for a specified period or duration.
-
D.
hasTourismAsMainEconomicActivity
Indicates that tourism is the primary source of economic activity or income for the referenced entity.
-
E.
hasTourismImpactOn
Indicates that one entity affects or influences the tourism levels, patterns, or attractiveness of another entity.
- 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_69e11e51fdec8190adfdf9f8a6362221 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b82549c8190943c0940bb90bafc |
completed | April 29, 2026, 1:14 a.m. |
| PD | Predicate disambiguation | batch_69e898b6eee08190ba673a0ee329e671 |
completed | April 22, 2026, 9:45 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:48 p.m.