Triple
T19282748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vlorë International Airport |
E482229
|
entity |
| Predicate | isLocatedInTourismArea |
P32586
|
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: [Vlorë International Airport, isLocatedInTourismArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLocatedInTourismArea Context triple: [Vlorë International Airport, isLocatedInTourismArea, yes]
-
A.
isPartOfTouristArea
chosen
Indicates that one entity is located within or belongs to a designated tourist area or tourist-focused region.
-
B.
containsTouristArea
Indicates that a place or region includes within its boundaries an area primarily designated or recognized for tourism activities.
-
C.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
-
D.
isTouristDestination
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
-
E.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbffda78819088bf8dbc61756831 |
completed | April 20, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69e4dd07a7208190afcd51ba1dc87c33 |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:30 p.m.