Triple
T26470968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sneath Lane trailhead |
E665897
|
entity |
| Predicate | elevationGainTo |
P30489
|
FINISHED |
| Object | Sweeney Ridge high point |
—
|
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: Sweeney Ridge high point | Statement: [Sneath Lane trailhead, elevationGainTo, Sweeney Ridge high point]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: elevationGainTo Context triple: [Sneath Lane trailhead, elevationGainTo, Sweeney Ridge high point]
-
A.
elevationGainFunction
Indicates a functional relationship that maps a path, route, or movement to the total amount of elevation gained along it.
-
B.
elevationGainRelativeToBase
Indicates the amount of elevation increase of something compared to a defined base level.
-
C.
hasApproxElevationGainFt
Indicates that one entity is associated with an approximate amount of elevation gain, measured in feet, relative to another context or reference.
-
D.
totalAscent
chosen
Indicates the total cumulative elevation gained over the course of a movement, route, or activity.
-
E.
elevationChange
Indicates a change in vertical position or altitude between two points or states.
- 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_69ee883f80dc819090e311b022b78e02 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
Created at: April 27, 2026, 12:19 a.m.