Triple
T14160314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stevens Park Golf Course |
E350918
|
entity |
| Predicate | hasGreensGrass |
P64312
|
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: [Stevens Park Golf Course, hasGreensGrass, Bentgrass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreensGrass Context triple: [Stevens Park Golf Course, hasGreensGrass, Bentgrass]
-
A.
hasMeadow
Indicates that one entity possesses, contains, or includes a meadow as part of its area or composition.
-
B.
hasGrassTypeGreens
chosen
Indicates that something possesses or includes green vegetation or grassy plant material.
-
C.
hasGreenSpaces
Indicates that an entity includes or is associated with areas of vegetation or natural greenery, such as parks, gardens, or lawns.
-
D.
isGreenSpaceFor
Indicates that one entity serves as a designated green or open space intended for use or benefit by another entity.
-
E.
hasVillageGreen
Indicates that one entity possesses or includes a village green as part of its area or facilities.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61393f308190bb357e2bd1916f94 |
completed | April 14, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:59 a.m.