Triple
T16225866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medusa Steel Coaster |
E393841
|
entity |
| Predicate | regionFirst |
P97650
|
FINISHED |
| Object | first Rocky Mountain Construction coaster in Latin America |
—
|
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: first Rocky Mountain Construction coaster in Latin America | Statement: [Medusa Steel Coaster, regionFirst, first Rocky Mountain Construction coaster in Latin America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionFirst Context triple: [Medusa Steel Coaster, regionFirst, first Rocky Mountain Construction coaster in Latin America]
-
A.
firstForRegion
chosen
Indicates that something is the earliest or primary instance of its kind within a specified region.
-
B.
region1
Indicates that one entity is the first or primary region associated with, containing, or encompassing another entity.
-
C.
regionFrom
Indicates that something originates from, is derived from, or is associated with a particular geographic or administrative region.
-
D.
regionSub
Indicates that one region is a subregion or contained part of another, larger region.
-
E.
regionOfState
Indicates that one administrative or geographical region is a subdivision or part of a larger state.
- 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.