Triple
T5549686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siwanoy Country Club |
E145494
|
entity |
| Predicate | hasCourseFeature |
P182
|
FINISHED |
| Object | tree-lined fairways |
—
|
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: tree-lined fairways | Statement: [Siwanoy Country Club, hasCourseFeature, tree-lined fairways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourseFeature Context triple: [Siwanoy Country Club, hasCourseFeature, tree-lined fairways]
-
A.
hasEducationalFeature
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
B.
hasFeature
chosen
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
C.
hasFeatureCode
Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
-
D.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
-
E.
hasCoursePattern
Indicates that an entity follows, is associated with, or is defined by a particular course structure or pattern.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe2aef481909944bc582c1f67a4 |
completed | March 22, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69c01b0e72f08190bf705d8fe1639401 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:35 p.m.