Triple
T15024684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betty Anderson |
E378177
|
entity |
| Predicate | targetAudienceRepresentation |
P10804
|
FINISHED |
| Object | American teenagers of the 1950s |
—
|
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: American teenagers of the 1950s | Statement: [Betty Anderson, targetAudienceRepresentation, American teenagers of the 1950s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAudienceRepresentation Context triple: [Betty Anderson, targetAudienceRepresentation, American teenagers of the 1950s]
-
A.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
B.
relatesToAudience
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
-
C.
typicalAudience
chosen
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
D.
targetAudienceOfOriginWork
Indicates the intended audience or demographic group for which the original work was created.
-
E.
representedTo
Indicates that one entity formally acted on behalf of or served as the representative of another entity in a given context or interaction.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7de117c8190a1b9fa8d1602057e |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:56 a.m.