Triple
T37320124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Picture for Munich |
E926451
|
entity |
| Predicate | nominatedFilmGenre |
P93695
|
FINISHED |
| Object | historical 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: historical drama film | Statement: [Academy Award for Best Picture for Munich, nominatedFilmGenre, historical drama film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nominatedFilmGenre Context triple: [Academy Award for Best Picture for Munich, nominatedFilmGenre, historical drama film]
-
A.
genreOfAwardedFilm
Indicates the genre category associated with a film that has received an award.
-
B.
sourceFilmGenre
chosen
Indicates that a film is classified as belonging to a particular genre.
-
C.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
D.
nominatedIn
Indicates that an entity has been formally put forward as a candidate for an award, position, or recognition within a specific event, context, or time period.
-
E.
filmGenreOfRelatedWork
Indicates that a work is related to another work through sharing or being associated with the same film 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_69f76eb28af88190b093b32e3fd614ab |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:16 p.m.