Triple
T17788528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cesar Glacier |
E444085
|
entity |
| Predicate | hasSnowLineContext |
P128925
|
FINISHED |
| Object | near the equatorial snow line on Mount Kenya |
—
|
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: near the equatorial snow line on Mount Kenya | Statement: [Cesar Glacier, hasSnowLineContext, near the equatorial snow line on Mount Kenya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSnowLineContext Context triple: [Cesar Glacier, hasSnowLineContext, near the equatorial snow line on Mount Kenya]
-
A.
hasLRTLine
Indicates that a location, station, or area is served by or lies along a specific light rail transit (LRT) line.
-
B.
hasDeFactoLine
Indicates that there exists an unofficial or non-legally recognized boundary or demarcation line functioning in practice between the related entities.
-
C.
hasSubsurfaceLines
Indicates that an entity possesses lines or features located beneath its visible surface.
-
D.
hasNearbyStateLine
Indicates that one location is situated close to the boundary line of a neighboring state.
-
E.
hasFrontLineFeature
Indicates that an entity possesses a specific characteristic or element located on its front side or leading edge.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4879524bc819090855ab5248c73db |
completed | April 19, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:12 a.m.