Triple
T4417823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayonne Golf Club |
E95019
|
entity |
| Predicate | turfTypeFairways |
P44260
|
FINISHED |
| Object | bentgrass |
—
|
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 | Statement: [Bayonne Golf Club, turfTypeFairways, bentgrass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turfTypeFairways Context triple: [Bayonne Golf Club, turfTypeFairways, bentgrass]
-
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.
beltwayType
Indicates the specific classification or type of a beltway (ring road) associated with a given roadway or area.
-
E.
trailNetworkType
Indicates the classification of a trail within a broader trail network, such as its role, category, or type of route in that system.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3551d5d7481908528c2de0a6fda06 |
completed | March 13, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:29 p.m.