Triple
T21870106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hehuanshan |
E539978
|
entity |
| Predicate | WulingPassElevation |
P79445
|
FINISHED |
| Object | approximately 3275 meters |
—
|
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 3275 meters | Statement: [Hehuanshan, WulingPassElevation, approximately 3275 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WulingPassElevation Context triple: [Hehuanshan, WulingPassElevation, approximately 3275 meters]
-
A.
elevationOfHighestPeak_ft
Indicates the height, in feet, of the tallest peak associated with the given entity.
-
B.
highestRoadPassIn
Indicates that a location contains the highest-elevation road pass within a specified area or region.
-
C.
mountainPassElevation_ft
Indicates the elevation, measured in feet, at which a mountain pass is located.
-
D.
peakElevationMetres
Indicates the maximum height of an entity above sea level, measured in metres.
-
E.
highestPassApproxElevation
chosen
Indicates the approximate elevation of the highest pass along a given route or within a specified area.
- 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f33509d08190b33775abb84d5255 |
completed | April 28, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:57 p.m.