Triple
T16853829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | vignette ads |
E409737
|
entity |
| Predicate | deviceFocus |
P125235
|
FINISHED |
| Object | mobile |
—
|
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: mobile | Statement: [vignette ads, deviceFocus, mobile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deviceFocus Context triple: [vignette ads, deviceFocus, mobile]
-
A.
importFocus
Indicates that attention, priority, or emphasis is being brought into or concentrated on a particular entity or aspect.
-
B.
screenTimeFocus
Indicates the amount or proportion of time an entity’s attention or activity is concentrated on a particular screen or digital display.
-
C.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
D.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
E.
stateOfFocus
Indicates the particular subject, area, or activity that an entity is currently concentrating attention or effort on.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37bbb80819086d844a313625cad |
completed | April 18, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e355722040819098830dabf207ecd6 |
completed | April 18, 2026, 9:57 a.m. |
Created at: April 10, 2026, 5:24 a.m.