Triple
T8668397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FuG 220 Lichtenstein SN-2 radar |
E205732
|
entity |
| Predicate | wavelengthApproximate |
P83980
|
FINISHED |
| Object | 3.3 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: 3.3 meters | Statement: [FuG 220 Lichtenstein SN-2 radar, wavelengthApproximate, 3.3 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wavelengthApproximate Context triple: [FuG 220 Lichtenstein SN-2 radar, wavelengthApproximate, 3.3 meters]
-
A.
wavelengthRangeLowerBoundMicrometers
Indicates the minimum wavelength value, expressed in micrometers, that defines the lower limit of a wavelength range for the related entity or measurement.
-
B.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
C.
supportsWavelengthRange
Indicates that an entity is capable of operating over, handling, or being compatible with a specified range of wavelengths.
-
D.
wavelengthDependence
Indicates that one quantity or effect varies as a function of the wavelength of radiation or a wave.
-
E.
approximateDiameter
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a48b548190b78259072b1224ee |
completed | March 31, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c330bc8190a9b644078881c6ff |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:31 p.m.