Triple
T9784420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American frontier captivity narratives |
E237456
|
entity |
| Predicate | hasTypicalAntagonist |
P58016
|
FINISHED |
| Object | Native American captor |
—
|
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: Native American captor | Statement: [American frontier captivity narratives, hasTypicalAntagonist, Native American captor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalAntagonist Context triple: [American frontier captivity narratives, hasTypicalAntagonist, Native American captor]
-
A.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
B.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
C.
antagonistInvolved
Indicates that an antagonist participates in, influences, or is otherwise actively involved in the referenced event or situation.
-
D.
primaryAntagonistType
chosen
Indicates the role or category of the main opposing force or adversary that serves as the central source of conflict.
-
E.
hasVillain
Indicates that one entity is the villain or primary antagonist associated with another entity.
- 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_69ca84da927881909bda80caecad6010 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda1b7740c8190bfb4997eb683d78a |
completed | April 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69cd03d77c6c81909b675955bf113320 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:27 p.m.