Triple
T649687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Defensive Aids Sub-System |
E11317
|
entity |
| Predicate | threatTypesDetected |
P1950
|
FINISHED |
| Object | radar emissions |
—
|
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: radar emissions | Statement: [Defensive Aids Sub-System, threatTypesDetected, radar emissions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatTypesDetected Context triple: [Defensive Aids Sub-System, threatTypesDetected, radar emissions]
-
A.
historicalThreat
Indicates that one entity posed a significant threat to another in the past, but is not necessarily a current or ongoing danger.
-
B.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
-
C.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
D.
riskType
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
E.
threat
Indicates a relationship where one entity expresses or poses potential harm, danger, or negative consequences toward 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f31e70c81909a2ac1d939f7ec07 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0eade081909c47e85ed55f808d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.