Triple
T506558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Whitney Trail |
E10514
|
entity |
| Predicate | summitElevation |
P14507
|
FINISHED |
| Object | approximately 14,505 feet |
—
|
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: approximately 14,505 feet | Statement: [Mount Whitney Trail, summitElevation, approximately 14,505 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: summitElevation Context triple: [Mount Whitney Trail, summitElevation, approximately 14,505 feet]
-
A.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
-
B.
rankInNorthAmericaByElevation
Indicates the relative position of a place in an ordered list of locations in North America based on their elevation.
-
C.
averageSummitTemperature
Indicates the typical or mean temperature measured at the summit of a location over a defined period.
-
D.
mountainSystem
Indicates a relationship where multiple mountains are grouped together as part of the same connected or coherent mountain system or range.
-
E.
highestPointRegion
Indicates that one location is the highest point within a specified region.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f14c83f08190b1028f4929866db4 |
completed | Feb. 28, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69a2edfce7a08190a408bc019de60d5d |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebbd70481908b462296671de67b |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.