Triple
T25430877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FUN |
E637248
|
entity |
| Predicate | airportSupportsTourism |
P33155
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [FUN, airportSupportsTourism, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportSupportsTourism Context triple: [FUN, airportSupportsTourism, yes]
-
A.
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.
-
B.
hasTourismFunction
chosen
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
C.
hasTourismIndustry
Indicates that a place or region possesses an established tourism industry, involving organized services and activities catering to visitors and travelers.
-
D.
hasTourismResource
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
-
E.
isTouristDestination
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 21, 2026, 1:58 p.m.