Triple
T12942445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outer Dark |
E309667
|
entity |
| Predicate | containsViolence |
P107612
|
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: [Outer Dark, containsViolence, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsViolence Context triple: [Outer Dark, containsViolence, true]
-
A.
containsGraphicViolence
Indicates that the subject includes depictions of explicit, intense, or realistic physical harm or brutality.
-
B.
violenceLevel
Indicates the degree or intensity of violent behavior, actions, or content present in or associated with an entity.
-
C.
hasTypeOfViolence
Indicates that an entity involves, exhibits, or is characterized by a specific kind or category of violent behavior or action.
-
D.
viewOnViolence
Indicates an entity’s stance, opinion, or attitude toward the use of violence.
-
E.
justifiesViolenceThrough
Indicates that one party legitimizes or defends the use of violence by appealing to, or reasoning through, another factor, belief, or circumstance.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97e5811f481908178fac6d2e0efcd |
completed | April 10, 2026, 10:48 p.m. |
Created at: April 9, 2026, 5:43 p.m.