Triple
T6527420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zosia Mamet |
E151339
|
entity |
| Predicate | notableVoiceWork |
P13156
|
FINISHED |
| Object | voice role in the animated series Regular Show |
—
|
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: voice role in the animated series Regular Show | Statement: [Zosia Mamet, notableVoiceWork, voice role in the animated series Regular Show]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableVoiceWork Context triple: [Zosia Mamet, notableVoiceWork, voice role in the animated series Regular Show]
-
A.
notableCharacterVoiced
chosen
Indicates that a notable character is voiced or performed by a specific voice actor or performer.
-
B.
notableVoiceActor
Indicates that one entity is a voice actor who is especially prominent or well-known for their work on the other entity.
-
C.
notableSpeechAssociated
Indicates that a notable or significant speech is associated with a particular entity, such as a person, event, or location.
-
D.
notableWorkCharacter
Indicates that a character appears in, is associated with, or plays a role in a particular notable work.
-
E.
notableWork
Indicates that one entity is a significant or well-known work (such as a book, artwork, or creation) produced by another 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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ada8a0e48190947616f3a09a2cba |
completed | March 27, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69c68abbc7148190a8270d47fe10cc31 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:45 p.m.