Triple
T33921886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luther universe |
E869636
|
entity |
| Predicate | antagonistArchetype |
P58016
|
FINISHED |
| Object | highly intelligent killers |
—
|
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: highly intelligent killers | Statement: [Luther universe, antagonistArchetype, highly intelligent killers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antagonistArchetype Context triple: [Luther universe, antagonistArchetype, highly intelligent killers]
-
A.
primaryAntagonistType
chosen
Indicates the role or category of the main opposing force or adversary that serves as the central source of conflict.
-
B.
antagonistActorRole
Indicates that an actor plays the role of an antagonist in a given work or context.
-
C.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
D.
antagonistAlterEgoOf
Indicates that one entity serves as the primary opposing force or enemy of another entity’s alternate identity or secret persona.
-
E.
antagonistStatus
Indicates that an entity holds an opposing or adversarial role, often acting as the main source of conflict relative to another entity or objective.
- 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_69f349992c508190aa4afa24a086cc8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:49 a.m.