Triple
T6346234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | June Lake Loop |
E142750
|
entity |
| Predicate | scenicBywayType |
P17006
|
FINISHED |
| Object | mountain road |
—
|
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: mountain road | Statement: [June Lake Loop, scenicBywayType, mountain road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scenicBywayType Context triple: [June Lake Loop, scenicBywayType, mountain road]
-
A.
isScenicByway
Indicates that a roadway is officially designated as a scenic byway, recognized for its notable visual, cultural, or natural appeal along its route.
-
B.
hasScenicByway
Indicates that one place, route, or area is connected to or includes a designated scenic byway.
-
C.
isPartOfScenicVista
Indicates that something is included within, or contributes to, a larger scenic vista or panoramic view.
-
D.
hasScenicDrive
chosen
Indicates that one entity offers or features a visually appealing or picturesque driving route associated with it.
-
E.
beltwayType
Indicates the specific classification or type of a beltway (ring road) associated with a given roadway or area.
- 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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067b907c4819085a3ea87589bc4be |
completed | March 22, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69c060ea1a988190889e47b7e0c819b8 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:31 p.m.