Triple
T9871905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prestwick Golf Club |
E239975
|
entity |
| Predicate | hasGreenkeepingPractice |
P4104
|
FINISHED |
| Object | traditional links maintenance |
—
|
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 links maintenance | Statement: [Prestwick Golf Club, hasGreenkeepingPractice, traditional links maintenance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenkeepingPractice Context triple: [Prestwick Golf Club, hasGreenkeepingPractice, traditional links maintenance]
-
A.
hasGrassTypeGreens
Indicates that something possesses or includes green vegetation or grassy plant material.
-
B.
hasGreenhouse
Indicates that an entity possesses or includes a greenhouse structure or facility.
-
C.
hasMeadow
Indicates that one entity possesses, contains, or includes a meadow as part of its area or composition.
-
D.
agriculturalPractice
chosen
Indicates a relationship where an entity engages in, applies, or is associated with a specific method or technique of agriculture or farming.
-
E.
hasGreenSpaces
Indicates that an entity includes or is associated with areas of vegetation or natural greenery, such as parks, gardens, or lawns.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f5cc948190b03186b867c92229 |
completed | April 2, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:36 p.m.