Triple
T2052370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Van Cortlandt Park |
E45596
|
entity |
| Predicate | golfCourseInstanceOf |
P35587
|
FINISHED |
| Object | one of the oldest public golf courses in the United States |
—
|
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: one of the oldest public golf courses in the United States | Statement: [Van Cortlandt Park, golfCourseInstanceOf, one of the oldest public golf courses in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: golfCourseInstanceOf Context triple: [Van Cortlandt Park, golfCourseInstanceOf, one of the oldest public golf courses in the United States]
-
A.
hasGolfCourse
Indicates that one entity possesses, contains, or includes a golf course as part of its facilities or attributes.
-
B.
numberOfGolfCourses
Indicates the total count of golf courses associated with a given entity.
-
C.
fairwayType
Indicates the specific kind or classification of a fairway associated with an entity.
-
D.
hasRacecourse
Indicates that an entity possesses, contains, or is associated with a racecourse facility or track.
-
E.
hasSportsVenueType
Indicates that a sports venue is classified as being of a specific type or category (e.g., stadium, arena, court).
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb99078d88190bc30fa4596f0bae8 |
completed | March 7, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_69abb7abba508190b872f345d3ba51bb |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb94ec400819097596732aabed854 |
completed | March 7, 2026, 5:36 a.m. |
Created at: March 4, 2026, 7:39 p.m.