Triple
T25608637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buckskin Pass |
E641980
|
entity |
| Predicate | isPartOfLoopRoute |
P6309
|
FINISHED |
| Object | Four Pass Loop around Maroon Bells |
—
|
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: Four Pass Loop around Maroon Bells | Statement: [Buckskin Pass, isPartOfLoopRoute, Four Pass Loop around Maroon Bells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfLoopRoute Context triple: [Buckskin Pass, isPartOfLoopRoute, Four Pass Loop around Maroon Bells]
-
A.
isPartOfRoute
chosen
Indicates that something (such as a segment, stop, or step) belongs to and is contained within a larger route.
-
B.
isOnCircularRoute
Indicates that an entity follows or belongs to a route that forms a closed loop, starting and ending at the same point.
-
C.
hasLoopRoad
Indicates that a location or area is connected by a road that forms a closed loop, beginning and ending at the same point.
-
D.
isLoopOf
Indicates that one entity represents a loop or cyclic structure corresponding to, derived from, or associated with another entity.
-
E.
isLoop
Indicates that something forms or behaves as a closed, repeating cycle or path that returns to its starting point.
- 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_69e75dc6ccf081908d49578fd36a76d5 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 21, 2026, 4:40 p.m.