Triple
T26760234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny Butterman |
E674780
|
entity |
| Predicate | favoriteFilmGenre |
P81962
|
FINISHED |
| Object | buddy cop movies |
—
|
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: buddy cop movies | Statement: [Danny Butterman, favoriteFilmGenre, buddy cop movies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: favoriteFilmGenre Context triple: [Danny Butterman, favoriteFilmGenre, buddy cop movies]
-
A.
favoriteGenre
chosen
Indicates that one entity’s preferred or most liked genre, among several possible genres, is the other entity.
-
B.
favoriteMovie
Indicates that one entity is the movie that another entity likes best among all movies.
-
C.
sourceFilmGenre
Indicates that a film is classified as belonging to a particular genre.
-
D.
keyGenreFilm
Indicates that a particular genre is the primary or defining genre associated with a given film.
-
E.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f61fd623bc819091df736cf3419b99 |
completed | May 2, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69f61b3d23f481908dfec27adace900a |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 3:57 a.m.