Triple
T35443237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 22nd Garrison Battalion (Australia) |
E1024408
|
entity |
| Predicate | prisonerNationalityGuarded |
P74411
|
FINISHED |
| Object | Japanese |
—
|
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: Japanese | Statement: [22nd Garrison Battalion (Australia), prisonerNationalityGuarded, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prisonerNationalityGuarded Context triple: [22nd Garrison Battalion (Australia), prisonerNationalityGuarded, Japanese]
-
A.
hasPrisonerNationality
chosen
Indicates that a prisoner is associated with a specific nationality.
-
B.
prisonerOf
Indicates that one entity is held in custody or confinement by another entity, typically under legal or authoritative control.
-
C.
prisonerType
Indicates the classification or category assigned to a prisoner within a correctional or detention system.
-
D.
notablePrisonerGuarded
Indicates that a guard was responsible for overseeing or guarding a prisoner who is considered notable or significant.
-
E.
prisonerSide
Indicates that one party in a conflict, case, or situation is aligned with or belongs to the side of the prisoner.
- 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_69f76df8089481909f0018266ee881b7 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7961e4f548190883f93c33bbcd44c |
completed | May 3, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:04 p.m.