Triple
T1785409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | surface-based launcher (NASAMS) |
E39379
|
entity |
| Predicate | threatTypeEngaged |
P32379
|
FINISHED |
| Object | fixed-wing aircraft |
—
|
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: fixed-wing aircraft | Statement: [surface-based launcher (NASAMS), threatTypeEngaged, fixed-wing aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatTypeEngaged Context triple: [surface-based launcher (NASAMS), threatTypeEngaged, fixed-wing aircraft]
-
A.
threatStatus
Indicates the level or category of risk or danger posed by one entity to another or to a defined system or environment.
-
B.
threatTypeAddressed
Indicates that a given action, measure, or entity is specifically intended to counter or mitigate a particular type of threat.
-
C.
threatCategory
Indicates the classification of a threat according to its type, severity, or nature within a defined risk or security framework.
-
D.
threat
Indicates a relationship where one entity expresses or poses potential harm, danger, or negative consequences toward another entity.
-
E.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab75457e54819096b8c6ae8c65550c |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61d165688190924962a98e07ff69 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab75444d28819091c393e62fc97f82 |
completed | March 7, 2026, 12:45 a.m. |
Created at: March 4, 2026, 7:31 p.m.