Triple
T1771393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Würzburg radar |
E38881
|
entity |
| Predicate | rangeAccuracy |
P5433
|
FINISHED |
| Object | about 25 m |
—
|
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 25 m | Statement: [Würzburg radar, rangeAccuracy, about 25 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rangeAccuracy Context triple: [Würzburg radar, rangeAccuracy, about 25 m]
-
A.
range
Indicates that a value, property, or effect extends between specified limits or over a specified interval or scope.
-
B.
rangeRestricted
Indicates that the relationship or action applies only within a specified, limited subset of a broader domain or scope.
-
C.
rangeCapability
chosen
Indicates the maximum distance or extent over which an entity can effectively operate, function, or exert its effect.
-
D.
rangeOf
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
-
E.
rangeSize
Indicates the extent or magnitude of the range over which something applies, varies, or is distributed.
- 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_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. |
Created at: March 4, 2026, 7:31 p.m.