Triple
T10009361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cars (film score) |
E198330
|
entity |
| Predicate | intendedForAudience |
P10804
|
FINISHED |
| Object | family audience |
—
|
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: family audience | Statement: [Cars (film score), intendedForAudience, family audience]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedForAudience Context triple: [Cars (film score), intendedForAudience, family audience]
-
A.
typicalAudience
chosen
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
B.
relatesToAudience
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
-
C.
hasEducationalAudience
Indicates that something is intended for or directed toward a specific educational audience or learner group.
-
D.
book3Audience
Indicates that a particular book is intended for or targeted toward a specific audience.
-
E.
secondaryAudience
Indicates that an entity is a secondary or additional intended audience or target group for another entity (such as a work, message, or product), beyond the primary audience.
- 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_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd38659c8190830d223edbfd74ec |
completed | April 2, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69cd1da2cf9081908a6c0eb5247d0bc2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:52 p.m.