Triple
T18811682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Letaba Rest Camp |
E460029
|
entity |
| Predicate | bookingThrough |
P92838
|
FINISHED |
| Object | SANParks reservation system |
—
|
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: SANParks reservation system | Statement: [Letaba Rest Camp, bookingThrough, SANParks reservation system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookingThrough Context triple: [Letaba Rest Camp, bookingThrough, SANParks reservation system]
-
A.
bookingModel
Indicates a relationship where an entity uses or is associated with a specific model or schema that defines how bookings are structured, processed, or represented.
-
B.
bookingHubFor
chosen
Indicates that one entity serves as the central platform or system through which bookings or reservations are made for another entity.
-
C.
reservationIn
Indicates that a reservation is associated with, or booked for, a specific place, service, or resource.
-
D.
reservationNear
Indicates that a reservation is located geographically close to a specified reference entity or place.
-
E.
reservationSystem
Indicates a system or process that manages the creation, modification, and tracking of reservations or bookings between parties.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3dc01248190ab1c8943d180ca05 |
completed | April 20, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.