Triple
T21188270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UK Quick Reaction Alert (South) |
E522141
|
entity |
| Predicate | threatTypes |
P50110
|
FINISHED |
| Object | unidentified military 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: unidentified military aircraft | Statement: [UK Quick Reaction Alert (South), threatTypes, unidentified military aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatTypes Context triple: [UK Quick Reaction Alert (South), threatTypes, unidentified military aircraft]
-
A.
threatType
chosen
Indicates the specific category or nature of a threat that one entity poses or represents in relation to another.
-
B.
threatCategory
Indicates the classification of a threat according to its type, severity, or nature within a defined risk or security framework.
-
C.
threatTypeAddressed
Indicates that a given action, measure, or entity is specifically intended to counter or mitigate a particular type of threat.
-
D.
threatFactors
Indicates that certain conditions, elements, or circumstances contribute to increasing the risk or likelihood of a harmful or adverse outcome.
-
E.
threatTypeMonitored
Indicates that a particular type of threat is being actively observed, tracked, or watched for by some monitoring process or system.
- 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7333403448190bcd9cc0805e414b5 |
completed | April 21, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69e5f6027c248190a170a36612bd337e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:07 p.m.