Triple
T20873990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cedar Fair, L.P. |
E513968
|
entity |
| Predicate | hasNotablePark |
P642
|
FINISHED |
| Object | Canada's Wonderland |
—
|
NE NERFINISHED |
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: Canada's Wonderland | Statement: [Cedar Fair, L.P., hasNotablePark, Canada's Wonderland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Canada's Wonderland Context triple: [Cedar Fair, L.P., hasNotablePark, Canada's Wonderland]
-
A.
Canada's Wonderland
chosen
Canada's Wonderland is a major amusement park near Toronto known for its large collection of roller coasters and family attractions.
-
B.
Wonderland Amusement Park
Wonderland Amusement Park was a historic amusement park in Revere, Massachusetts, known for its early 20th-century rides, attractions, and seaside entertainment.
-
C.
Wonderland Amusement Park
Wonderland Amusement Park is a regional family amusement park in Amarillo, Texas, featuring a variety of rides, games, and seasonal attractions.
-
D.
Wet’n’Wild Toronto
Wet’n’Wild Toronto is a large outdoor water park in Brampton, Ontario, featuring numerous water slides, pools, and family attractions.
-
E.
Phantasialand
Phantasialand is a major German theme park known for its highly themed lands and innovative roller coasters and attractions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f675cc8190b4e745225b62eb66 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c46639308190a616193f3975d453 |
completed | April 21, 2026, 12:27 a.m. |
Created at: April 16, 2026, 12:45 p.m.