Triple
T16225960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joker (roller coaster, Six Flags México) |
E393843
|
entity |
| Predicate | hasOnRideExperience |
P98191
|
FINISHED |
| Object | randomized flipping |
—
|
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: randomized flipping | Statement: [Joker (roller coaster, Six Flags México), hasOnRideExperience, randomized flipping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnRideExperience Context triple: [Joker (roller coaster, Six Flags México), hasOnRideExperience, randomized flipping]
-
A.
hasRideExperience
chosen
Indicates that one entity has undergone, participated in, or possesses experience with a particular ride or riding activity in relation to another entity.
-
B.
hasRollerCoaster
Indicates that one entity possesses, contains, or features a roller coaster as part of it.
-
C.
hasNotableRide
Indicates that an entity is associated with a particularly remarkable or well-known ride or attraction.
-
D.
hasThrillRides
Indicates that an entity offers or includes thrill rides as part of its features or attractions.
-
E.
hasDarkRide
Indicates that one entity features or includes a dark ride attraction associated with the other entity.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d25f8bc81909aa59b794a528db2 |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.