Triple
T10106518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabale und Liebe |
E216334
|
entity |
| Predicate | antagonistSocialClass |
P92454
|
FINISHED |
| Object | nobility |
—
|
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: nobility | Statement: [Kabale und Liebe, antagonistSocialClass, nobility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antagonistSocialClass Context triple: [Kabale und Liebe, antagonistSocialClass, nobility]
-
A.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
B.
antagonistOccupation
Indicates the role, job, or professional activity that the antagonist character performs.
-
C.
antagonistInvolved
Indicates that an antagonist participates in, influences, or is otherwise actively involved in the referenced event or situation.
-
D.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
E.
primaryAntagonistType
Indicates the role or category of the main opposing force or adversary that serves as the central source of conflict.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0c8a0408190be886ec1013a5208 |
completed | April 2, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd5150ae98819086c4f822114b4e2c |
completed | April 1, 2026, 5:09 p.m. |
Created at: March 30, 2026, 9:03 p.m.