Triple
T7968942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrow Development |
E185275
|
entity |
| Predicate | spaceMountainCategory |
P63190
|
FINISHED |
| Object | indoor space-themed roller coaster |
—
|
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: indoor space-themed roller coaster | Statement: [Arrow Development, spaceMountainCategory, indoor space-themed roller coaster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spaceMountainCategory Context triple: [Arrow Development, spaceMountainCategory, indoor space-themed roller coaster]
-
A.
coasterType
chosen
Indicates the specific category or style of a coaster that characterizes its design or function.
-
B.
rollerCoasterType
Indicates that one entity is classified as a specific type or category of roller coaster in relation to another entity.
-
C.
partOfAttractionType
Indicates that one attraction type is a component or subset of a broader, more general attraction type.
-
D.
themeParkComplex
Indicates a relationship where one entity is a theme park complex that encompasses or is composed of the other entity or entities.
-
E.
attractionType
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
- 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_69ca8297699481909b75a405f01e03af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bd1c9a081909759e5bf5237204e |
completed | March 31, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69cb047a8e4c81909b79e0f0bf56440c |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:13 p.m.