Triple
T1782266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knickebein |
E39314
|
entity |
| Predicate | countermeasureType |
P1135
|
FINISHED |
| Object | radio jamming |
—
|
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: radio jamming | Statement: [Knickebein, countermeasureType, radio jamming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countermeasureType Context triple: [Knickebein, countermeasureType, radio jamming]
-
A.
attackType
Indicates the specific method, style, or category of attack used in an aggressive or hostile action between entities.
-
B.
typeOfDefense
chosen
Indicates the specific kind or category of defense employed or possessed in a given context.
-
C.
protectionType
Indicates the kind or method of protection that is applied to or associated with an entity.
-
D.
militaryMeasure
Indicates a relationship where an entity undertakes, imposes, or is subject to a specific military-related action, policy, or operational measure.
-
E.
threatTypeAddressed
Indicates that a given action, measure, or entity is specifically intended to counter or mitigate a particular type of threat.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab74dc9d1481908084ef07872a71f8 |
completed | March 7, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69aa61cf3ca881908641fd73ce2f7c9d |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.