Triple
T14684588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DC Rivals HyperCoaster |
E344876
|
entity |
| Predicate | hasRiderOption |
P63715
|
FINISHED |
| Object | backwards-facing seats |
—
|
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: backwards-facing seats | Statement: [DC Rivals HyperCoaster, hasRiderOption, backwards-facing seats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiderOption Context triple: [DC Rivals HyperCoaster, hasRiderOption, backwards-facing seats]
-
A.
hasOwnerRider
Indicates that an entity (such as an animal or vehicle) has a specific person who both owns it and rides or uses it.
-
B.
hasSubRide
Indicates that a ride or journey is composed of, or includes, one or more smaller component rides or segments.
-
C.
riderType
Indicates the category or role of a rider in relation to a ride, transport service, or vehicle (e.g., passenger, driver, courier).
-
D.
hasBoardingOption
chosen
Indicates that an entity offers or is associated with a particular way or method by which passengers or items can board or be taken on.
-
E.
hasRidingAssociation
Indicates an association where one entity is related to another through the act or context of riding (e.g., serving as rider, mount, or riding partner).
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb56bdb8081909ff86440ba20fb1f |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de6579fb7881909becc8f5822b39d4 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.