Triple
T25250850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bozcaada |
E632735
|
entity |
| Predicate | hasTourismPattern |
P82318
|
FINISHED |
| Object | seasonal tourism peak in summer |
—
|
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: seasonal tourism peak in summer | Statement: [Bozcaada, hasTourismPattern, seasonal tourism peak in summer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTourismPattern Context triple: [Bozcaada, hasTourismPattern, seasonal tourism peak in summer]
-
A.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
B.
hasTouristVisits
Indicates that one entity experiences or records visits from tourists to another entity.
-
C.
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.
-
D.
hasTourismStyle
chosen
Indicates the type or style of tourism associated with or characteristic of a particular entity.
-
E.
hasTourismResource
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
- 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_69e75a8fdd3881909ba0b05aa5da92a7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 1:11 p.m.