Triple
T26326842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Super Mario Bros. Super Show! |
E662274
|
entity |
| Predicate | animatedVoiceActor |
P83203
|
FINISHED |
| Object | Lou Albano as animated Mario |
—
|
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: Lou Albano as animated Mario | Statement: [The Super Mario Bros. Super Show!, animatedVoiceActor, Lou Albano as animated Mario]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: animatedVoiceActor Context triple: [The Super Mario Bros. Super Show!, animatedVoiceActor, Lou Albano as animated Mario]
-
A.
characterTypeVoiced
Indicates that one character serves as the voice actor or vocal performer for another character.
-
B.
voiceActorOfPerformer
Indicates that one performer provides the voice for a character or role portrayed by another performer.
-
C.
hasVoiceActing
chosen
Indicates that one entity provides voice performance for a character, role, or work associated with another entity.
-
D.
voiceActorFemale
Indicates that the subject is a female voice actor who provides the voice for the specified character or role.
-
E.
notableVoiceActor
Indicates that one entity is a voice actor who is especially prominent or well-known for their work on the other entity.
- 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_69ee812f32748190871d970c4e2a8ddf |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60f65f9f48190ba299fb3e435e67a |
completed | May 2, 2026, 2:51 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 10:31 p.m.