Triple
T26579511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Berelc |
E667038
|
entity |
| Predicate | notableForTargetAudience |
P140994
|
FINISHED |
| Object | younger audiences |
—
|
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: younger audiences | Statement: [Paris Berelc, notableForTargetAudience, younger audiences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableForTargetAudience Context triple: [Paris Berelc, notableForTargetAudience, younger audiences]
-
A.
notableAudience
chosen
Indicates that an entity is especially well-known, relevant, or targeted among a particular audience or group of people.
-
B.
notableTarget
Indicates that the subject is particularly significant, prominent, or noteworthy with respect to the specified target.
-
C.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
D.
relatesToAudience
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
-
E.
notableTargetType
Indicates that the subject is notable or significant specifically in relation to entities of the given target type.
- 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_69ee9cfb7e548190b60a9031182f5a7e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fef112398081909237c3872345968b |
completed | May 9, 2026, 8:32 a.m. |
| PD | Predicate disambiguation | batch_69feefb14ec08190ab401987d8c84a23 |
completed | May 9, 2026, 8:26 a.m. |
Created at: April 27, 2026, 2:02 a.m.