Triple
T3305472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Zuckerman |
E69437
|
entity |
| Predicate | notableGenreWorkedIn |
P12590
|
FINISHED |
| Object | adult animated sitcom |
—
|
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: adult animated sitcom | Statement: [David Zuckerman, notableGenreWorkedIn, adult animated sitcom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableGenreWorkedIn Context triple: [David Zuckerman, notableGenreWorkedIn, adult animated sitcom]
-
A.
notableWorkGenre
chosen
Indicates that a particular work is recognized as notable for an entity and specifies the genre to which that work belongs.
-
B.
notableTypeOfWork
Indicates that a work is a significant or defining example within a particular type or category of work associated with an entity.
-
C.
notableWorkWith
Indicates a relationship where two or more entities are recognized for having collaborated on or been jointly associated with a significant work or project.
-
D.
notableWorkIn
Indicates that an entity is known for or associated with a significant work, contribution, or achievement in a particular field or context.
-
E.
notableProductionType
Indicates that the subject is particularly known for producing or creating instances of the specified type.
- 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0c9470881908c36c1984fdbb67b |
completed | March 8, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69ada42625308190be257f16a623a410 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.