Triple
T33439205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Born to Kill |
E856312
|
entity |
| Predicate | hasFilmNoirStyle |
P41012
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Born to Kill, hasFilmNoirStyle, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmNoirStyle Context triple: [Born to Kill, hasFilmNoirStyle, true]
-
A.
hasFilmStyle
chosen
Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
-
B.
hasTheatricalStyle
Indicates that one entity possesses, exhibits, or is characterized by a particular theatrical style associated with another entity.
-
C.
hasScreenplayStyle
Indicates that an entity is associated with or characterized by a particular style or manner of screenplay writing.
-
D.
hasDramaticStyle
Indicates that an entity employs or is characterized by a theatrical, emotionally intense, or striking manner of expression or presentation.
-
E.
hasComicStyle
Indicates that one entity is characterized by, presented in, or associated with a particular comic or cartoon-like visual style defined by the other entity.
- 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_69f34971b75881908be360bb041f003c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
Created at: May 1, 2026, 1:37 a.m.