Triple
T457501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FrontlineMakeshiftCamps |
E7264
|
entity |
| Predicate | detaineeStatus |
P13715
|
FINISHED |
| Object | Prisoners of war |
—
|
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: Prisoners of war | Statement: [FrontlineMakeshiftCamps, detaineeStatus, Prisoners of war]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: detaineeStatus Context triple: [FrontlineMakeshiftCamps, detaineeStatus, Prisoners of war]
-
A.
placeOfDetention
Indicates the location or facility where an entity is or was held in detention.
-
B.
detainedBy
Indicates that an entity is being held in custody or confinement by another entity, typically an authority or controlling party.
-
C.
detainedAfter
Indicates that one entity is held in custody or confinement following another specified event or action.
-
D.
criminalStatus
Indicates the legal condition of an entity with respect to criminal law, such as whether they are accused, convicted, or cleared of a crime.
-
E.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa3163081909acff040a22bd559 |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede614b88190be07425f5535f56d |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ee8b56d08190bd625626353d01b4 |
completed | Feb. 28, 2026, 1:32 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.