Triple
T16248081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bel Air Country Club golf course |
E394427
|
entity |
| Predicate | courseUse |
P122340
|
FINISHED |
| Object | private |
—
|
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: private | Statement: [Bel Air Country Club golf course, courseUse, private]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courseUse Context triple: [Bel Air Country Club golf course, courseUse, private]
-
A.
usesCourse
Indicates that one entity makes use of, applies, or relies on a particular course in some context or activity.
-
B.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
-
C.
course
Indicates that an entity is an academic class or unit of instruction offered within an educational program.
-
D.
courseClass
Indicates that a particular course is classified as belonging to a specific academic class or category.
-
E.
courseLoad
Indicates the quantity or intensity of academic work (such as number of courses or credits) assigned to or undertaken by an individual or program.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245942460819080897afad0d2fe09 |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:04 a.m.