Triple
T32944498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sankt Leon-Rot |
E842762
|
entity |
| Predicate | hasGolfFacility |
P4286
|
FINISHED |
| Object | Golf Club St. Leon-Rot |
—
|
NE NERFINISHED |
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: Golf Club St. Leon-Rot | Statement: [Sankt Leon-Rot, hasGolfFacility, Golf Club St. Leon-Rot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGolfFacility Context triple: [Sankt Leon-Rot, hasGolfFacility, Golf Club St. Leon-Rot]
-
A.
hasGolfCourse
chosen
Indicates that one entity possesses, contains, or includes a golf course as part of its facilities or attributes.
-
B.
hasGolfCourseCluster
Indicates that an entity is associated with or contains a group or concentration of golf courses in a particular area.
-
C.
hasGolfCourseBrand
Indicates that an entity is associated with or operates a specific brand of golf course.
-
D.
hasGolfDestination
Indicates that one entity serves as a golf-related destination or location for another entity.
-
E.
golfCourseUse
Indicates that an entity is used as a golf course or for playing golf.
- 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_69f34949727c81909d195c97de3341c8 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:20 a.m.