Triple
T24896521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Course at Royal Troon |
E623157
|
entity |
| Predicate | hasClubhouseAccess |
P159389
|
FINISHED |
| Object | Royal Troon Golf Club clubhouse |
—
|
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: Royal Troon Golf Club clubhouse | Statement: [Old Course at Royal Troon, hasClubhouseAccess, Royal Troon Golf Club clubhouse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClubhouseAccess Context triple: [Old Course at Royal Troon, hasClubhouseAccess, Royal Troon Golf Club clubhouse]
-
A.
hasClubhouses
Indicates that an entity possesses, manages, or is associated with one or more clubhouses.
-
B.
hasClubhouseArchitect
Indicates that an entity’s clubhouse was designed or planned by a specified architect.
-
C.
hasClub
Indicates that an entity is associated with or belongs to a particular club.
-
D.
hasKeyClub
Indicates that an entity is associated with or belongs to a Key Club organization or group.
-
E.
hasHumanAccess
Indicates that a human is able to access, use, or interact with the referenced entity or resource.
- 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_69e2fac597708190a922bf39a49ec70a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f584f07b648190aee894c1d5320bc3 |
completed | May 2, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
| PDg | Predicate description generation | batch_69f55e497fa081909bc59a7b92c5df59 |
completed | May 2, 2026, 2:15 a.m. |
Created at: April 18, 2026, 5:26 a.m.