Triple
T1074739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rügen |
E23809
|
entity |
| Predicate | hasResortArchitecture |
P5770
|
FINISHED |
| Object | Baltic Sea spa architecture |
—
|
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: Baltic Sea spa architecture | Statement: [Rügen, hasResortArchitecture, Baltic Sea spa architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResortArchitecture Context triple: [Rügen, hasResortArchitecture, Baltic Sea spa architecture]
-
A.
hasArchitecturalFeature
Indicates that one entity possesses, includes, or is characterized by a specific architectural feature or element.
-
B.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
C.
hasPopularResort
Indicates that a location or area contains or is associated with a resort that is widely visited or well-liked.
-
D.
hasSisterResort
Indicates that one resort is formally associated with another as its sister property, typically under common ownership or branding.
-
E.
architecturalConcept
chosen
Indicates that one entity represents or embodies an architectural concept in relation to another entity.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92cbfd481909e2f928c1d06ebaa |
completed | March 1, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69a4b73ba8208190be7f3cef8c18689b |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.