Triple
T32641694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boy and the Beast |
E834494
|
entity |
| Predicate | hasEnglishDubCastMember |
P175851
|
FINISHED |
| Object | John Swasey |
—
|
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: John Swasey | Statement: [The Boy and the Beast, hasEnglishDubCastMember, John Swasey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishDubCastMember Context triple: [The Boy and the Beast, hasEnglishDubCastMember, John Swasey]
-
A.
hasDubActor
chosen
Indicates that one entity serves as the dubbing voice actor for another entity in a particular work or version.
-
B.
dubbedFor
Indicates that one media work has been voice-dubbed to create a version suitable for another language, region, or audience.
-
C.
voicedByInLatinAmericanSpanishDub
Indicates that an entity serves as the voice actor for another entity specifically in the Latin American Spanish dubbed version of a work.
-
D.
voicedByInEuropeanSpanishDub
Indicates that one entity serves as the voice actor for another entity specifically in the European Spanish dubbed version of a work.
-
E.
languageDubbedIn
Indicates that the content’s audio has been dubbed into the specified language.
- 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_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 1, 2026, 1:07 a.m.