Triple
T33465396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | What's Opera, Doc? |
E857028
|
entity |
| Predicate | voiceActorForBugsBunny |
P140664
|
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: [What's Opera, Doc?, voiceActorForBugsBunny, Mel Blanc]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voiceActorForBugsBunny Context triple: [What's Opera, Doc?, voiceActorForBugsBunny, Mel Blanc]
-
A.
voiceActorForRabbit
chosen
Indicates that one entity serves as the voice actor for a rabbit character associated with the other entity.
-
B.
voiceActorForWinnieThePooh
Indicates that one entity serves as the voice actor portraying the character Winnie the Pooh in a performance or production.
-
C.
voiceActorForMickeyMouse
Indicates that one entity serves as the voice actor who performs the character Mickey Mouse in audio or audiovisual works.
-
D.
voiceActorOfPerformer
Indicates that one performer provides the voice for a character or role portrayed by another performer.
-
E.
voiceActorForMario
Indicates that one entity serves as the voice actor who provides the spoken or vocal performance for the character Mario in a work or series of works.
- 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f75dc25fa08190b371faf36d9fb72c |
completed | May 3, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f758586534819083e91172f4bf5098 |
completed | May 3, 2026, 2:14 p.m. |
Created at: May 1, 2026, 1:37 a.m.