Triple
T22345090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Askernish Golf Club |
E552370
|
entity |
| Predicate | usesGreenType |
P24953
|
FINISHED |
| Object | traditional fescue greens |
—
|
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: traditional fescue greens | Statement: [Askernish Golf Club, usesGreenType, traditional fescue greens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesGreenType Context triple: [Askernish Golf Club, usesGreenType, traditional fescue greens]
-
A.
hasGreenType
chosen
Indicates that an entity possesses or is associated with a type classified as green.
-
B.
greenUsedFor
Indicates that something green serves a particular purpose or function for something else.
-
C.
usesBrandColor
Indicates that one entity applies or displays another entity’s official brand color in its appearance, design, or materials.
-
D.
traditionalGreen
Indicates that something adheres to or embodies a customary or historically established form of the color green.
-
E.
greenRepresents
Indicates that one entity uses the color green to symbolize, denote, or stand for another entity or concept.
- 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157975db481909db65ff4d8505bbd |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.