Triple
T37122695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tellico Plains, Tennessee |
E919302
|
entity |
| Predicate | hasNearbyScenicByway |
P118030
|
FINISHED |
| Object | Cherohala Skyway |
—
|
NE NERFINISHED |
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: Cherohala Skyway | Statement: [Tellico Plains, Tennessee, hasNearbyScenicByway, Cherohala Skyway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyScenicByway Context triple: [Tellico Plains, Tennessee, hasNearbyScenicByway, Cherohala Skyway]
-
A.
hasScenicByway
Indicates that one place, route, or area is connected to or includes a designated scenic byway.
-
B.
isScenicByway
Indicates that a roadway is officially designated as a scenic byway, recognized for its notable visual, cultural, or natural appeal along its route.
-
C.
hasScenicSectionNear
Indicates that one location includes a visually appealing or picturesque segment situated close to another specified location.
-
D.
nearScenicRoute
chosen
Indicates that one entity is located close to a route or path that is considered scenic or visually appealing.
-
E.
hasScenicPassNearby
Indicates that a location is situated close to a notable scenic pass, such as a mountain or landscape viewpoint route.
- 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_69f76e9c57148190ba789dd059645bb9 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a008ac37dc081908d360574912f40ec |
completed | May 10, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_6a008a67d73881909855ab4cfca3c399 |
completed | May 10, 2026, 1:38 p.m. |
Created at: May 3, 2026, 4:15 p.m.