Triple
T921733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump National Doral Miami |
E19898
|
entity |
| Predicate | hasGolfCourseType |
P4286
|
FINISHED |
| Object | 18-hole championship courses |
—
|
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: 18-hole championship courses | Statement: [Trump National Doral Miami, hasGolfCourseType, 18-hole championship courses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGolfCourseType Context triple: [Trump National Doral Miami, hasGolfCourseType, 18-hole championship courses]
-
A.
hasGolfCourse
chosen
Indicates that one entity possesses, contains, or includes a golf course as part of its facilities or attributes.
-
B.
fairwayType
Indicates the specific kind or classification of a fairway associated with an entity.
-
C.
hasGardenType
Indicates that an entity possesses or is associated with a garden of a specified type.
-
D.
hasRacecourse
Indicates that an entity possesses, contains, or is associated with a racecourse facility or track.
-
E.
hasCricketGround
Indicates that one entity possesses, contains, or includes a cricket ground as part of its facilities or attributes.
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b313cb908190ad78b3a54e4f2eb7 |
completed | March 1, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69a4b295b02481908e5f53bfcb83cc94 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.