Triple
T27461400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lt. Col. Kirby Yorke |
E692754
|
entity |
| Predicate | fictionalConflict |
P176713
|
FINISHED |
| Object | Indian Wars |
—
|
NE NERFINISHED |
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: Indian Wars | Statement: [Lt. Col. Kirby Yorke, fictionalConflict, Indian Wars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalConflict Context triple: [Lt. Col. Kirby Yorke, fictionalConflict, Indian Wars]
-
A.
storyConflict
Indicates a relationship where a story contains or centers around a central problem, opposition, or tension that drives its plot.
-
B.
hasFictionalUniverseConflict
Indicates that there is a conflict or incompatibility between the fictional universes associated with the related entities.
-
C.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
-
D.
mainConflict
Indicates the primary opposing force, problem, or struggle that drives tension and narrative progression between entities or sides.
-
E.
storyConflictSource
Indicates the source or cause from which a story’s central conflict arises.
- 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_69ef5207903881909427745cda05d27a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69f6e60109648190947a64ca4ce81a3a |
completed | May 3, 2026, 6:06 a.m. |
Created at: April 27, 2026, 12:50 p.m.