Triple
T20003173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Do Not Disturb While Driving in iOS 11 |
E494385
|
entity |
| Predicate | autoReplyTrigger |
P69330
|
FINISHED |
| Object | incoming text message |
—
|
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: incoming text message | Statement: [Do Not Disturb While Driving in iOS 11, autoReplyTrigger, incoming text message]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: autoReplyTrigger Context triple: [Do Not Disturb While Driving in iOS 11, autoReplyTrigger, incoming text message]
-
A.
typicalTrigger
Indicates that one entity commonly or characteristically causes, initiates, or brings about the occurrence of another entity or event.
-
B.
triggeredResponse
chosen
Indicates that one entity’s action or event causes another entity to produce a specific reaction or output.
-
C.
triggered
Indicates that one entity causes an event, action, or process involving another entity to start or occur.
-
D.
responseTool
Indicates a tool, method, or mechanism used to produce, deliver, or manage a response in a given context.
-
E.
JesusResponsePattern
Indicates the characteristic way Jesus typically responds in a given situation, including his manner, tone, or type of action taken.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a2e34481908a495cc5d077c41f |
completed | April 20, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:33 p.m.