Triple
T12999441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Formula Rossa |
E322128
|
entity |
| Predicate | regionRecord |
P107759
|
FINISHED |
| Object | fastest roller coaster in the Middle East |
—
|
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: fastest roller coaster in the Middle East | Statement: [Formula Rossa, regionRecord, fastest roller coaster in the Middle East]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionRecord Context triple: [Formula Rossa, regionRecord, fastest roller coaster in the Middle East]
-
A.
regionOfState
Indicates that one administrative or geographical region is a subdivision or part of a larger state.
-
B.
regionSub
Indicates that one region is a subregion or contained part of another, larger region.
-
C.
region1
Indicates that one entity is the first or primary region associated with, containing, or encompassing another entity.
-
D.
regionException
Indicates an exception or exclusion to a rule, condition, or classification that applies specifically to a certain region or set of regions.
-
E.
regionReference
Indicates that one entity refers to, points to, or is associated with a specific region or area defined by another entity.
- F. None of above. chosen
Provenance (4 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7b268c8190b8bb855e9de23c3b |
completed | April 10, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69d97dc153a081909d13a694993f074a |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97e74283c819082e69ac3554fa7d8 |
completed | April 10, 2026, 10:49 p.m. |
Created at: April 9, 2026, 8:46 p.m.