Triple
T33481399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Haiyaha |
E857482
|
entity |
| Predicate | trailDistanceFromBearLakeTrailhead |
P63487
|
FINISHED |
| Object | roughly 2 miles one way |
—
|
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: roughly 2 miles one way | Statement: [Lake Haiyaha, trailDistanceFromBearLakeTrailhead, roughly 2 miles one way]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trailDistanceFromBearLakeTrailhead Context triple: [Lake Haiyaha, trailDistanceFromBearLakeTrailhead, roughly 2 miles one way]
-
A.
approximateRoundTripDistanceFromTrailhead
Indicates the estimated total distance of a complete out-and-back journey measured from the trailhead.
-
B.
trailDistanceApprox
chosen
Indicates that the distance along a trail between two locations is approximately a specified value, allowing for some margin of error.
-
C.
trailDistanceContext
Indicates the contextual distance or separation between entities along a trail, path, or route.
-
D.
distanceToSaranacLake
Indicates the spatial distance between a given entity and Saranac Lake.
-
E.
hasApproximateRoundTripDistanceFromMaroonLake
Indicates that an entity has an approximate total round-trip distance measured from Maroon Lake.
- 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_69f3497472508190b300ebd3fd402367 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e52fd4bc8190a18d0cd7dad5c6bf |
completed | May 3, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:38 a.m.