Triple
T3045461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schöner Brunnen |
E83434
|
entity |
| Predicate | hasLocalLegend |
P1582
|
FINISHED |
| Object | turning the golden ring brings good luck |
—
|
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: turning the golden ring brings good luck | Statement: [Schöner Brunnen, hasLocalLegend, turning the golden ring brings good luck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalLegend Context triple: [Schöner Brunnen, hasLocalLegend, turning the golden ring brings good luck]
-
A.
hasLegendAssociatedWith
chosen
Indicates that something is connected to or accompanied by a traditional story, myth, or legend.
-
B.
isLocalLandmark
Indicates that something is recognized as a notable or significant landmark within a specific local area or community.
-
C.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
-
D.
hasLandmarkUnderManagement
Indicates that an entity is responsible for managing or overseeing a particular landmark.
-
E.
hasLocalChaptersIn
Indicates that an organization maintains one or more local chapters or branches within a specified geographic area or location.
- 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_69ad8b24924c8190a9bb6f61d519e4ae |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b602ed881909a72662eb544866b |
completed | March 8, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69ad961fc62c819087c4c3a44b00847d |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.