Triple
T25608626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buckskin Pass |
E641980
|
entity |
| Predicate | hasApproximateRoundTripDistanceFromMaroonLake |
P163842
|
FINISHED |
| Object | 9 to 10 miles |
—
|
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: 9 to 10 miles | Statement: [Buckskin Pass, hasApproximateRoundTripDistanceFromMaroonLake, 9 to 10 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateRoundTripDistanceFromMaroonLake Context triple: [Buckskin Pass, hasApproximateRoundTripDistanceFromMaroonLake, 9 to 10 miles]
-
A.
hasNearbyLake
Indicates that one entity is located close to or in the vicinity of a lake.
-
B.
distanceToSaranacLake
Indicates the spatial distance between a given entity and Saranac Lake.
-
C.
hasNearbyLakeRegion
Indicates that one region is located close to a lake or lake-dominated area.
-
D.
approximateRoundTripDistanceFromTrailhead
Indicates the estimated total distance of a complete out-and-back journey measured from the trailhead.
-
E.
hasHighestPointNear
Indicates that one entity’s highest point is located close to another specified entity or location.
- F. None of above. chosen
Provenance (4 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_69f6416fbf4081909b0913c337927fc4 |
completed | May 2, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 21, 2026, 4:40 p.m.