Triple
T28418835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Distraction |
E719884
|
entity |
| Predicate | originalChannelTargetAudience |
P61787
|
FINISHED |
| Object | adult viewers |
—
|
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: adult viewers | Statement: [Distraction, originalChannelTargetAudience, adult viewers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalChannelTargetAudience Context triple: [Distraction, originalChannelTargetAudience, adult viewers]
-
A.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
B.
targetQualification
Indicates that one entity specifies or defines the required qualification or eligibility criteria for another entity.
-
C.
targetAudienceOfOriginWork
chosen
Indicates the intended audience or demographic group for which the original work was created.
-
D.
targetAudienceTheme
Indicates the thematic focus or type of audience that a work, message, or product is specifically intended to appeal to or address.
-
E.
targetChannel
Indicates the specific channel or medium through which an action, message, or effect is directed toward its intended recipient.
- 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_69eff6f1c5088190bc24bfbf92f9c017 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fecb4d02f881909a9ee97ce98000d5 |
completed | May 9, 2026, 5:51 a.m. |
| PD | Predicate disambiguation | batch_69fec9846c1c8190b317f0711f0755db |
completed | May 9, 2026, 5:43 a.m. |
Created at: April 28, 2026, 1:32 a.m.