Triple
T6093273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Street (Canada's Wonderland) |
E135816
|
entity |
| Predicate | guestService |
P31921
|
FINISHED |
| Object | ticketing and entry validation |
—
|
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: ticketing and entry validation | Statement: [International Street (Canada's Wonderland), guestService, ticketing and entry validation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: guestService Context triple: [International Street (Canada's Wonderland), guestService, ticketing and entry validation]
-
A.
guestFlow
Indicates the movement or progression of guests through a space, process, or experience over time.
-
B.
returnsAsGuestIn
Indicates that an entity comes back to participate or appear again in a context, but specifically in the role or capacity of a guest rather than a regular or primary member.
-
C.
serviceUser
Indicates that one entity is a user or consumer of a service provided by another entity.
-
D.
hasFrontDesk
Indicates that one entity provides or is equipped with a front desk service or reception area for another entity.
-
E.
supportsGuest
chosen
Indicates that one entity provides assistance, resources, or accommodation to another entity in the role of a guest.
- 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057ac8c7481909fb22cf157be45ce |
completed | March 22, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:12 p.m.