Triple
T251152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney's Magnolia Golf Course |
E5148
|
entity |
| Predicate | hasPracticeFacility |
P2836
|
FINISHED |
| Object | driving range |
—
|
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: driving range | Statement: [Disney's Magnolia Golf Course, hasPracticeFacility, driving range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPracticeFacility Context triple: [Disney's Magnolia Golf Course, hasPracticeFacility, driving range]
-
A.
hasFacilityType
chosen
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
B.
hasNotableFacility
Indicates that an entity possesses or hosts a facility that is of particular significance, prominence, or interest.
-
C.
hasDiscoveryFacility
Indicates that an entity has, is associated with, or is served by a facility where discoveries (such as scientific, medical, or technological findings) are made or were made.
-
D.
operatesFacility
Indicates that an entity is responsible for running, managing, or controlling the operations of a particular facility.
-
E.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d38aba8819081d0958eb60ce27e |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b665f8c8190aac6fcbba2a0eebb |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.