Triple
T1771392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Würzburg radar |
E38881
|
entity |
| Predicate | elevationAccuracy |
P31701
|
FINISHED |
| Object | about 0.2 degrees |
—
|
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 0.2 degrees | Statement: [Würzburg radar, elevationAccuracy, about 0.2 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: elevationAccuracy Context triple: [Würzburg radar, elevationAccuracy, about 0.2 degrees]
-
A.
elevation
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
B.
elevationType
Indicates the kind or classification of elevation associated with an entity, such as how its height or altitude is characterized.
-
C.
elevationContext
Indicates the contextual relationship between an entity and its elevation or vertical position relative to a reference point or environment.
-
D.
hasAverageElevation
Indicates that an entity is characterized by a specific mean height above a defined reference level, typically sea level.
-
E.
elevationChange
Indicates a change in vertical position or altitude between two points or states.
- F. None of above. chosen
Provenance (4 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab39fc2c448190bfaf1ee8d474632a |
completed | March 6, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69aa61cbb1288190a7ba38b61905f578 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab39faf69c8190bae98d3e3911078f |
completed | March 6, 2026, 8:32 p.m. |
Created at: March 4, 2026, 7:31 p.m.