Triple
T5549684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siwanoy Country Club |
E145494
|
entity |
| Predicate | courseRenovation |
P65316
|
FINISHED |
| Object | multiple renovations over 20th century |
—
|
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: multiple renovations over 20th century | Statement: [Siwanoy Country Club, courseRenovation, multiple renovations over 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courseRenovation Context triple: [Siwanoy Country Club, courseRenovation, multiple renovations over 20th century]
-
A.
courseSetting
Indicates the context or environment in which a course is delivered or conducted.
-
B.
course
Indicates that an entity is an academic class or unit of instruction offered within an educational program.
-
C.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
-
D.
courseShape
Indicates the geometric layout or configuration that defines the path or outline of a course.
-
E.
courseDesigner
Indicates that one entity is responsible for creating, planning, or structuring the content and format of a course for another entity.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69c01f051e508190b3886d87b4afdd0b |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:35 p.m.