Triple
T8668398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FuG 220 Lichtenstein SN-2 radar |
E205732
|
entity |
| Predicate | maximumRangeApproximate |
P14301
|
FINISHED |
| Object | 4 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: 4 km | Statement: [FuG 220 Lichtenstein SN-2 radar, maximumRangeApproximate, 4 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumRangeApproximate Context triple: [FuG 220 Lichtenstein SN-2 radar, maximumRangeApproximate, 4 km]
-
A.
rangeOf
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
-
B.
maximumReach
chosen
Indicates the greatest extent, distance, or limit that something can reach or influence within a given context.
-
C.
maximumExtent
Indicates the greatest or furthest degree, size, or range to which something can extend or apply within a given context.
-
D.
approximateRadius
Indicates that one entity specifies or provides an estimated value for the radius of another entity.
-
E.
maximumNumber
Indicates that one entity specifies the highest allowable or observed quantity, value, or count associated with another entity.
- 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_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. |
Created at: March 30, 2026, 6:31 p.m.