Triple
T26784578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limone Piemonte railway station |
E670343
|
entity |
| Predicate | isInTourismArea |
P32586
|
FINISHED |
| Object | Alpine tourism area |
—
|
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: Alpine tourism area | Statement: [Limone Piemonte railway station, isInTourismArea, Alpine tourism area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInTourismArea Context triple: [Limone Piemonte railway station, isInTourismArea, Alpine tourism area]
-
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.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
D.
isScenicArea
Indicates that a location is recognized as a scenic area, typically valued for its natural beauty or visually appealing surroundings.
-
E.
isWithinPark
Indicates that one entity is located inside the boundaries of a park that contains it.
- 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_69eeb31d45f8819089f52ebdbc556218 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6383625cc8190aa223d8ef655743c |
completed | May 2, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69f63709e4848190b5cf322e06b23fb6 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 4:12 a.m.