Triple
T32553852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actor (Joaquin Phoenix) |
E832042
|
entity |
| Predicate | genreOfAwardedFilm |
P179848
|
FINISHED |
| Object | psychological thriller |
—
|
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: psychological thriller | Statement: [Academy Award for Best Actor (Joaquin Phoenix), genreOfAwardedFilm, psychological thriller]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfAwardedFilm Context triple: [Academy Award for Best Actor (Joaquin Phoenix), genreOfAwardedFilm, psychological thriller]
-
A.
genreOfAwards
Indicates the type or category of awards associated with a given work, event, or entity.
-
B.
keyGenreFilm
Indicates that a particular genre is the primary or defining genre associated with a given film.
-
C.
sourceFilmGenre
Indicates that a film is classified as belonging to a particular genre.
-
D.
filmGenreOfRelatedWork
Indicates that a work is related to another work through sharing or being associated with the same film genre.
-
E.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
- F. None of above. chosen
Provenance (4 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f727afd5d88190ad48735cd1b32787 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72737c42c8190a3f781a5e98868ff |
completed | May 3, 2026, 10:45 a.m. |
| PDg | Predicate description generation | batch_69f727ad9ff88190ba8069dd48b2e98f |
completed | May 3, 2026, 10:47 a.m. |
Created at: May 1, 2026, 1:02 a.m.