Triple
T5664785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonel Jack |
E124831
|
entity |
| Predicate | protagonistMoralArc |
P34394
|
FINISHED |
| Object | from criminality to repentance |
—
|
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: from criminality to repentance | Statement: [Colonel Jack, protagonistMoralArc, from criminality to repentance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistMoralArc Context triple: [Colonel Jack, protagonistMoralArc, from criminality to repentance]
-
A.
characterArc
Indicates the developmental journey or transformation a character undergoes over the course of a narrative.
-
B.
characterArcElement
Indicates that one element is a component or stage within a character’s overall developmental arc or transformation.
-
C.
moralNarrativeRole
Indicates the role an entity plays within a moral storyline or ethical framing, such as being portrayed as virtuous, villainous, victimized, or morally ambiguous.
-
D.
hasMoralArc
chosen
Indicates that something follows a discernible trajectory of moral development, progress, or decline over time.
-
E.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0236d3f94819095111c41a323612d |
completed | March 22, 2026, 5:14 p.m. |
| PD | Predicate disambiguation | batch_69c021ba4ec481909db8cdbf0e907dd6 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:43 p.m.