Triple
T2928584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Araucanía International Airport |
E78903
|
entity |
| Predicate | hasElevationAboveSeaLevel |
P221
|
FINISHED |
| Object | 304 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: 304 meters | Statement: [La Araucanía International Airport, hasElevationAboveSeaLevel, 304 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElevationAboveSeaLevel Context triple: [La Araucanía International Airport, hasElevationAboveSeaLevel, 304 meters]
-
A.
hasAverageElevation
Indicates that an entity is characterized by a specific mean height above a defined reference level, typically sea level.
-
B.
elevation
chosen
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
C.
elevationAboveLake
Indicates the vertical height or altitude of something relative to the surface level of a specified lake.
-
D.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
E.
highestElevationApprox
Indicates that an entity has an approximate value for the maximum elevation reached within its spatial or conceptual extent.
- 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97ff0ddc8190acba9863bbe4f54b |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9606e8348190bb19df33a2709674 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:55 p.m.