Triple
T6748350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilmette Golf Club |
E154275
|
entity |
| Predicate | hasFairwayType |
P44260
|
FINISHED |
| Object | bentgrass fairways |
—
|
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: bentgrass fairways | Statement: [Wilmette Golf Club, hasFairwayType, bentgrass fairways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFairwayType Context triple: [Wilmette Golf Club, hasFairwayType, bentgrass fairways]
-
A.
fairwayType
Indicates the specific kind or classification of a fairway associated with an entity.
-
B.
fairwayGrassType
chosen
Indicates the type or variety of grass used on a golf course fairway.
-
C.
hasYardage
Indicates that something possesses or is associated with a specific measured distance or length, typically expressed in yards.
-
D.
hasWaterHazards
Indicates that the subject contains or is associated with one or more water-based obstacles or danger areas.
-
E.
hasGrassTypeGreens
Indicates that something possesses or includes green vegetation or grassy plant material.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:11 p.m.