Triple
T33854387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gary Oldman as Norman Stansfield |
E867729
|
entity |
| Predicate | violenceLevelInStory |
P80416
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Gary Oldman as Norman Stansfield, violenceLevelInStory, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: violenceLevelInStory Context triple: [Gary Oldman as Norman Stansfield, violenceLevelInStory, high]
-
A.
violenceLevel
chosen
Indicates the degree or intensity of violent behavior, actions, or content present in or associated with an entity.
-
B.
containsViolence
Indicates that the subject includes, depicts, or involves acts of physical harm, aggression, or violent behavior.
-
C.
violenceLevelComparedToOriginal
Indicates the degree to which the level of violence in one version differs from that in the original version.
-
D.
containsGraphicViolence
Indicates that the subject includes depictions of explicit, intense, or realistic physical harm or brutality.
-
E.
typeOfViolenceAddressed
Indicates the specific form or category of violence that is being targeted, dealt with, or addressed in a given context.
- 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_69f349943ccc8190a3c41a3e0ae46cbf |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70076bdec8190a109af85bed04c90 |
completed | May 3, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:47 a.m.