Triple
T21527592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lhotse Face |
E531135
|
entity |
| Predicate | lowerElevationApprox |
P45909
|
FINISHED |
| Object | 6500 metres |
—
|
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: 6500 metres | Statement: [Lhotse Face, lowerElevationApprox, 6500 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowerElevationApprox Context triple: [Lhotse Face, lowerElevationApprox, 6500 metres]
-
A.
elevationLowerThan
Indicates that the elevation of one entity is lower than the elevation of another entity.
-
B.
elevationMinApprox
Indicates an approximate value for the minimum elevation associated with an entity or location.
-
C.
lowerLocation
Indicates that one entity is located physically below or at a lower vertical position relative to another entity.
-
D.
elevationApproxMeters
chosen
Indicates the approximate elevation of an entity above sea level, measured in meters.
-
E.
lowestPointsNear
Indicates that one entity identifies or specifies the locations of the lowest points in elevation or value in the vicinity of another entity.
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee88522e948190b9fa5a3587f32eae |
completed | April 26, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69e6320043bc81909417c41a718652ba |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:26 p.m.