Triple
T2555531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SmartScreen |
E56721
|
entity |
| Predicate | warningType |
P40820
|
FINISHED |
| Object | informational warnings |
—
|
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: informational warnings | Statement: [SmartScreen, warningType, informational warnings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: warningType Context triple: [SmartScreen, warningType, informational warnings]
-
A.
warnsAbout
Indicates that one entity alerts or cautions another entity about a potential danger, risk, or problem.
-
B.
alertMethod
Indicates the method or channel through which an alert or notification is delivered from a source to a recipient.
-
C.
threatCategory
Indicates the classification of a threat according to its type, severity, or nature within a defined risk or security framework.
-
D.
issueType
Indicates the specific category or classification assigned to an issue within a tracking or management context.
-
E.
trapType
Indicates the specific kind or category of trap associated with an entity or situation.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0c8b6f08190a68645db3e8b779a |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd5a1cd508190a660b9a3c6b7cbcb |
completed | March 7, 2026, 7:37 a.m. |
Created at: March 6, 2026, 9:48 p.m.