Triple
T36376443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2/30th Battalion |
E895915
|
entity |
| Predicate | prisonerOfWarExperience |
P6764
|
FINISHED |
| Object | many personnel held in Changi Prison |
—
|
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: many personnel held in Changi Prison | Statement: [2/30th Battalion, prisonerOfWarExperience, many personnel held in Changi Prison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prisonerOfWarExperience Context triple: [2/30th Battalion, prisonerOfWarExperience, many personnel held in Changi Prison]
-
A.
prisonersOfWar
chosen
Indicates a relationship where certain individuals are held in custody by an enemy during an armed conflict as prisoners of war.
-
B.
WWIIExperience
Indicates that an entity has a specific involvement, role, or personal history related to World War II.
-
C.
numberOfPrisonersDuringWar
Indicates the count of prisoners held during a specified war or wartime period.
-
D.
shareWarExperience
Indicates that one entity communicates or recounts its experiences of war to another entity.
-
E.
capturedInWar
Indicates that one entity was taken prisoner or seized by another entity as a result of armed conflict or wartime actions.
- 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_69f76e5115588190ad8738860b7bc68b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb3ff1b08190802b1063d55d3923 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a611a081908dd6aec1df3f4d7f |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:10 p.m.