Triple
T810300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Cybersecurity Protection System |
E17527
|
entity |
| Predicate | threatTypeAddressed |
P19863
|
FINISHED |
| Object | malware |
—
|
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: malware | Statement: [National Cybersecurity Protection System, threatTypeAddressed, malware]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatTypeAddressed Context triple: [National Cybersecurity Protection System, threatTypeAddressed, malware]
-
A.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
B.
threat
Indicates a relationship where one entity expresses or poses potential harm, danger, or negative consequences toward another entity.
-
C.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
D.
historicalThreat
Indicates that one entity posed a significant threat to another in the past, but is not necessarily a current or ongoing danger.
-
E.
transportThreat
Indicates a relationship where an entity moves or conveys a threat from one place or context to another.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab4c7418819085cb64c6bf5fa70c |
completed | March 1, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69a4aa73df08819096d0553a4b2509de |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab4781c88190ae36906251347cdc |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:38 p.m.