Triple
T4049025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clingmans Dome |
E84137
|
entity |
| Predicate | viewRadius |
P23277
|
FINISHED |
| Object | up to 100 miles in clear conditions |
—
|
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: up to 100 miles in clear conditions | Statement: [Clingmans Dome, viewRadius, up to 100 miles in clear conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewRadius Context triple: [Clingmans Dome, viewRadius, up to 100 miles in clear conditions]
-
A.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
B.
ringRadius
Indicates the size of a ring by specifying the distance from its center to its outer edge.
-
C.
approximateRadius
chosen
Indicates that one entity specifies or provides an estimated value for the radius of another entity.
-
D.
viewOver
Indicates that one entity has a visual perspective overlooking or facing another entity, typically providing a vantage point onto it.
-
E.
viewingDistanceFromFalls
Indicates the distance from which an observer views or experiences the falls.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb82d1a08190aa8c5c48d368b58b |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef900386481909d04555a9ec9b0e3 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.