Triple
T13136012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Zissou |
E312083
|
entity |
| Predicate | filmGenreOfWorkHeAppearsIn |
P41614
|
FINISHED |
| Object | comedy-drama |
—
|
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: comedy-drama | Statement: [Steve Zissou, filmGenreOfWorkHeAppearsIn, comedy-drama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmGenreOfWorkHeAppearsIn Context triple: [Steve Zissou, filmGenreOfWorkHeAppearsIn, comedy-drama]
-
A.
genreOfWorkActedIn
chosen
Indicates that an entity is the genre category of a work in which another entity performed or acted.
-
B.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
C.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or work.
-
D.
genreOfWorkDirected
Indicates that a person has directed a work (such as a film, show, or performance) belonging to a specified genre.
-
E.
producedFilmType
Indicates that an entity (such as a person or organization) was responsible for producing a film of a specified type or category.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b53fbc8190a0f209c32a00f6cb |
completed | April 10, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69d9804543cc8190a23cd7da59a12a7b |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:08 p.m.