Triple
T5752036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gloria (Barbie 2023 character) |
E126874
|
entity |
| Predicate | targetAudienceConnection |
P62009
|
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: [Gloria (Barbie 2023 character), targetAudienceConnection, adult viewers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAudienceConnection Context triple: [Gloria (Barbie 2023 character), targetAudienceConnection, adult viewers]
-
A.
relatesToAudience
chosen
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
-
B.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
C.
targetsGroup
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
D.
targetsUseCase
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
-
E.
connectsCommunity
Indicates a relationship where an entity links or brings together members or groups within a community, fostering interaction or cohesion among them.
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b52663c8190ab44258468d4296d |
completed | March 22, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c021ca61688190875bd6107161c284 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:48 p.m.