Triple
T33315759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Encino Golf Course |
E853009
|
entity |
| Predicate | hasGolfCartRental |
P82860
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Encino Golf Course, hasGolfCartRental, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGolfCartRental Context triple: [Encino Golf Course, hasGolfCartRental, yes]
-
A.
hasCartRental
chosen
Indicates that an entity provides or is associated with the service of renting carts to another entity.
-
B.
hasRentalCarCenter
Indicates that a location or facility includes or is associated with a rental car center where vehicles can be rented.
-
C.
hasRentalShop
Indicates that one entity operates, owns, or is associated with a rental shop used to provide items or services for rent to others.
-
D.
offersEquipmentRental
Indicates that one entity provides equipment to another entity for temporary use in exchange for a fee or under a rental agreement.
-
E.
hasGolfCourse
Indicates that one entity possesses, contains, or includes a golf course as part of its facilities or attributes.
- 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_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:33 a.m.