Triple
T5485259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Torrey Pines Golf Course |
E123563
|
entity |
| Predicate | hasGrassTypeFairways |
P44260
|
FINISHED |
| Object | Kikuyu grass |
—
|
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: Kikuyu grass | Statement: [Torrey Pines Golf Course, hasGrassTypeFairways, Kikuyu grass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrassTypeFairways Context triple: [Torrey Pines Golf Course, hasGrassTypeFairways, Kikuyu grass]
-
A.
fairwayGrassType
chosen
Indicates the type or variety of grass used on a golf course fairway.
-
B.
fairwayType
Indicates the specific kind or classification of a fairway associated with an entity.
-
C.
hasInnerTurfCourse
Indicates that something (typically a race track or stadium) possesses an inner turf course located within its main track or field.
-
D.
hasYardage
Indicates that something possesses or is associated with a specific measured distance or length, typically expressed in yards.
-
E.
hasGolfCourse
Indicates that one entity possesses, contains, or includes a golf course 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd93e5d0f08190a6cc9fc408b7c5bb |
completed | March 20, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69bd91a73b148190a865243536a4fe76 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:10 p.m.