Triple
T7969010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrow Development |
E185277
|
entity |
| Predicate | knownForAttractionType |
P8648
|
FINISHED |
| Object | steel tubular track coasters |
—
|
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: steel tubular track coasters | Statement: [Arrow Development, knownForAttractionType, steel tubular track coasters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForAttractionType Context triple: [Arrow Development, knownForAttractionType, steel tubular track coasters]
-
A.
attractionType
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
-
B.
isMajorAttractionFor
Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
-
C.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
-
D.
hasAttractionType
chosen
Indicates that one entity is associated with a specific kind or category of attraction (e.g., tourist, cultural, natural).
-
E.
relatedAttraction
Indicates that one attraction is associated with or connected to another attraction in some relevant way.
- 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.