Triple
T30664000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cedar Point Shores Waterpark |
E780606
|
entity |
| Predicate | hasLockerRental |
P122390
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Cedar Point Shores Waterpark, hasLockerRental, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLockerRental Context triple: [Cedar Point Shores Waterpark, hasLockerRental, true]
-
A.
hasCartRental
Indicates that an entity provides or is associated with the service of renting carts to another entity.
-
B.
hasLockers
chosen
Indicates that one entity provides or contains lockers that are available for use by another entity.
-
C.
hasUmbrellasForRent
Indicates that one entity offers umbrellas available for temporary rental use by others.
-
D.
hasRentalShop
Indicates that one entity operates, owns, or is associated with a rental shop used to provide items or services for rent to others.
-
E.
offersEquipmentRental
Indicates that one entity provides equipment to another entity for temporary use in exchange for a fee or under a rental agreement.
- 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_69f224a6d10481909290be1a00fc83b3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: April 29, 2026, 8:31 p.m.