Triple
T38552102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leon Schlesinger Productions |
E925137
|
entity |
| Predicate | usedVoiceActor |
P39669
|
FINISHED |
| Object | Mel Blanc |
—
|
NE NERFINISHED |
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: Mel Blanc | Statement: [Leon Schlesinger Productions, usedVoiceActor, Mel Blanc]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedVoiceActor Context triple: [Leon Schlesinger Productions, usedVoiceActor, Mel Blanc]
-
A.
previouslyVoicedBy
Indicates that one entity served as the voice actor for another entity at some earlier time, but no longer does so in the current context.
-
B.
voiceActorOfPerformer
Indicates that one performer provides the voice for a character or role portrayed by another performer.
-
C.
hasVoiceActing
Indicates that one entity provides voice performance for a character, role, or work associated with another entity.
-
D.
notableVoiceActor
chosen
Indicates that one entity is a voice actor who is especially prominent or well-known for their work on the other entity.
-
E.
voicedByAlsoKnownFor
Indicates that the person who voices a character is also notably recognized for another specific role or work.
- 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_69f76eaeb69c8190b367df9330d6f6af |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.