Triple
T135683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SOFIA airborne observatory operations |
E2740
|
entity |
| Predicate | altitudeRange |
P1977
|
FINISHED |
| Object | about 11 to 14 kilometers |
—
|
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: about 11 to 14 kilometers | Statement: [SOFIA airborne observatory operations, altitudeRange, about 11 to 14 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: altitudeRange Context triple: [SOFIA airborne observatory operations, altitudeRange, about 11 to 14 kilometers]
-
A.
typicalElevationRange
chosen
Indicates the usual range of elevation values within which something commonly occurs or exists.
-
B.
elevation
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
C.
mountainRange
Indicates that one entity is a mountain range that the other entity is part of, associated with, or located in.
-
D.
mountainRangeType
Indicates the classification or category of a mountain range based on its geological or geographical type.
-
E.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a3ad908190b6a8652f09ae0cbb |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25651b9048190a6277b7fec98c1ea |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.