Triple
T35317853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Tateshina |
E1019952
|
entity |
| Predicate | elevationMetersApprox |
P45909
|
FINISHED |
| Object | 2530 |
—
|
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: 2530 | Statement: [Mount Tateshina, elevationMetersApprox, 2530]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: elevationMetersApprox Context triple: [Mount Tateshina, elevationMetersApprox, 2530]
-
A.
elevationApproxMeters
chosen
Indicates the approximate elevation of an entity above sea level, measured in meters.
-
B.
elevationFeetApproximate
Indicates the approximate elevation of an entity above sea level, measured in feet.
-
C.
elevationCoverageApproximate
Indicates an approximate or estimated representation of how elevation values are covered or distributed over a given area or dataset.
-
D.
hasApproxElevationFeet
Indicates that an entity is associated with an elevation value measured in feet that is approximate rather than exact.
-
E.
elevation
Indicates the vertical height or altitude of one entity relative to a reference level or 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_69f76de9d45c81908a2ed0956b448b65 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:03 p.m.