Triple
T22258262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shoot 'Em Up |
E550146
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Angry Films |
—
|
NE NERFINISHED |
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: Angry Films | Statement: [Shoot 'Em Up, productionCompany, Angry Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angry Films Context triple: [Shoot 'Em Up, productionCompany, Angry Films]
-
A.
Angry Films
chosen
Angry Films is a film and television production company best known for producing genre-driven action, science fiction, and comic book adaptations.
-
B.
Goddamn Films
Goddamn Films is a film and television production company known for its involvement in high-profile projects such as the Marvel series "Daredevil."
-
C.
Cruel and Unusual Films
Cruel and Unusual Films is a film production company co-founded by director Zack Snyder, known for producing several of his visually stylized action and superhero movies.
-
D.
Dirty Films
Dirty Films is an independent film and television production company co-founded by actress Cate Blanchett, known for producing a range of critically acclaimed projects.
-
E.
Furious Films
Furious Films is a film production company best known for its involvement in genre and science fiction cinema, including work on the movie "Species II."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c4bff48190b4be83f5f7677ac8 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.