Triple
T12635328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zafferana Etnea |
E301746
|
entity |
| Predicate | hasTouristRole |
P33155
|
FINISHED |
| Object | base for excursions to Mount Etna |
—
|
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: base for excursions to Mount Etna | Statement: [Zafferana Etnea, hasTouristRole, base for excursions to Mount Etna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTouristRole Context triple: [Zafferana Etnea, hasTouristRole, base for excursions to Mount Etna]
-
A.
hasTouristProfile
Indicates that an entity possesses characteristics, data, or attributes defining it as a tourist or related to tourism behavior.
-
B.
hasTouristVisits
Indicates that one entity experiences or records visits from tourists to another entity.
-
C.
hasTourismFunction
chosen
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
D.
hasTouristRoute
Indicates that a location or site is connected to or included in a designated tourist route or itinerary.
-
E.
hasTouristRank
Indicates that an entity is assigned a specific rank or rating based on its attractiveness or importance as a tourist destination.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:16 p.m.