Triple
T9341592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MUTO |
E224774
|
entity |
| Predicate | threatLevelInUniverse |
P27859
|
FINISHED |
| Object | global threat |
—
|
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: global threat | Statement: [MUTO, threatLevelInUniverse, global threat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatLevelInUniverse Context triple: [MUTO, threatLevelInUniverse, global threat]
-
A.
threatLevelDescription
Indicates a textual description that characterizes the severity or nature of a threat level associated with an entity or situation.
-
B.
threatCategory
Indicates the classification of a threat according to its type, severity, or nature within a defined risk or security framework.
-
C.
threatType
Indicates the specific category or nature of a threat that one entity poses or represents in relation to another.
-
D.
threatStatus
chosen
Indicates the level or category of risk or danger posed by one entity to another or to a defined system or environment.
-
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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4bafa9108190889397614756020d |
completed | April 1, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69cc7a66aef08190b8d668cff5b04f5f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:40 p.m.