Triple
T37506442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Divine Justice |
E932104
|
entity |
| Predicate | combatTraining |
P188691
|
FINISHED |
| Object | Dora Milaje training |
—
|
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: Dora Milaje training | Statement: [Queen Divine Justice, combatTraining, Dora Milaje training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combatTraining Context triple: [Queen Divine Justice, combatTraining, Dora Milaje training]
-
A.
trainingGround
Indicates a location or context where entities engage in practice, drills, or preparation activities to develop or improve skills.
-
B.
militaryTrainingType
Indicates the specific kind or category of military training associated with an entity or event.
-
C.
combatApplication
Indicates the application or use of something (such as skills, tactics, or equipment) within a combat or fighting context.
-
D.
militaryTrainingFocus
Indicates that the primary emphasis or specialization of a subject’s military training is on a particular skill, domain, or operational area.
-
E.
trainingGroundFor
Indicates that one entity serves as a place or context where another entity is trained, prepared, or developed.
- 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_69f76ec5268481909ea01c73aeeefd42 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbacaea12c8190a4c99e64335f0e7e |
completed | May 6, 2026, 9:03 p.m. |
Created at: May 3, 2026, 4:17 p.m.