Triple
T12893274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Moscow as young Josh Baskin |
E308421
|
entity |
| Predicate | targetAudienceRelation |
P62009
|
FINISHED |
| Object | relatableChildProtagonist |
—
|
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: relatableChildProtagonist | Statement: [David Moscow as young Josh Baskin, targetAudienceRelation, relatableChildProtagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAudienceRelation Context triple: [David Moscow as young Josh Baskin, targetAudienceRelation, relatableChildProtagonist]
-
A.
relationshipToAudience
Indicates the nature or type of connection an entity has with a specified audience, such as role, stance, or relevance.
-
B.
relatesToAudience
chosen
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
-
C.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
D.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
E.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971484aa08190a8adfafabe600903 |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:40 p.m.