Triple
T1003232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coast Starlight |
E21649
|
entity |
| Predicate | scenicReputation |
P6652
|
FINISHED |
| Object | one of Amtrak's most scenic routes |
—
|
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: one of Amtrak's most scenic routes | Statement: [Coast Starlight, scenicReputation, one of Amtrak's most scenic routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scenicReputation Context triple: [Coast Starlight, scenicReputation, one of Amtrak's most scenic routes]
-
A.
hasScenicValue
chosen
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
B.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
C.
hasMountainScenery
Indicates that a place or area features views or landscapes dominated by mountains.
-
D.
hasScenicDrive
Indicates that one entity offers or features a visually appealing or picturesque driving route associated with it.
-
E.
landscapeStyle
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fe0a548190aee8abf1890e141e |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b1f4f88190822598cfd2a0fd2b |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.