Triple
T34249468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Vitelloni (film score) |
E878698
|
entity |
| Predicate | associatedGenreOfRelatedFilm |
P146635
|
FINISHED |
| Object | Italian drama film |
—
|
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: Italian drama film | Statement: [I Vitelloni (film score), associatedGenreOfRelatedFilm, Italian drama film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedGenreOfRelatedFilm Context triple: [I Vitelloni (film score), associatedGenreOfRelatedFilm, Italian drama film]
-
A.
accompaniesGenreOfFilm
Indicates that one thing is typically associated with or goes along with a particular film genre.
-
B.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or work.
-
C.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
D.
genreRelation
Indicates a relationship where one entity is categorized as having, belonging to, or being associated with a particular genre defined by another entity.
-
E.
hasGenreOfWorkItAppearsIn
chosen
Indicates that an entity is associated with the genre of the work in which it appears.
- 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_69f349b3618481909df955b063f305b2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:56 a.m.