Triple
T3070778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Cinque Ports Golf Club |
E64013
|
entity |
| Predicate | fairwayGrassType |
P44260
|
FINISHED |
| Object | links turf |
—
|
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: links turf | Statement: [Royal Cinque Ports Golf Club, fairwayGrassType, links turf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fairwayGrassType Context triple: [Royal Cinque Ports Golf Club, fairwayGrassType, links turf]
-
A.
fairwayType
Indicates the specific kind or classification of a fairway associated with an entity.
-
B.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
C.
fieldDesign
Indicates a relationship where an entity is responsible for planning, arranging, or specifying the layout and structure of a particular field or area.
-
D.
hasYardage
Indicates that something possesses or is associated with a specific measured distance or length, typically expressed in yards.
-
E.
stateGrass
Indicates that a specified location or region has grass as its primary or notable ground cover.
- F. None of above. chosen
Provenance (4 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_69ad857a8aec8190bfdfd9c14554ac5a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada14b366881908e2ca104e5f38251 |
completed | March 8, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69ad9625b30c819099ef9349c91d7b25 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f7630c81908e1ca8a69611cff6 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 3:02 p.m.