Triple
T1750241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freya radar |
E38422
|
entity |
| Predicate | rangeResolution |
P25684
|
FINISHED |
| Object | about 1–2 km |
—
|
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 1–2 km | Statement: [Freya radar, rangeResolution, about 1–2 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rangeResolution Context triple: [Freya radar, rangeResolution, about 1–2 km]
-
A.
hasSpatialResolution
chosen
Indicates that something is characterized by a specific level of spatial detail or granularity at which it can represent or distinguish features in space.
-
B.
rangeCapability
Indicates the maximum distance or extent over which an entity can effectively operate, function, or exert its effect.
-
C.
rangeSize
Indicates the extent or magnitude of the range over which something applies, varies, or is distributed.
-
D.
spectralResolution
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
E.
range
Indicates that a value, property, or effect extends between specified limits or over a specified interval or scope.
- 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba6a63f588190b53b39c6b97d74f4 |
completed | March 7, 2026, 4:16 a.m. |
| PD | Predicate disambiguation | batch_69aa61c7ef4c8190abec87c96a787d82 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.