Triple
T722051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werl Prison |
E14637
|
entity |
| Predicate | hasInmateType |
P121
|
FINISHED |
| Object | adult male prisoners |
—
|
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: adult male prisoners | Statement: [Werl Prison, hasInmateType, adult male prisoners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInmateType Context triple: [Werl Prison, hasInmateType, adult male prisoners]
-
A.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
-
B.
detaineeStatus
Indicates the current legal or custodial condition of a person being detained, such as whether they are in custody, released, or under a specific detention regime.
-
C.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
D.
placeOfDetention
Indicates the location or facility where an entity is or was held in detention.
-
E.
hasMemberType
chosen
Indicates that an entity includes or is associated with members belonging to a specified type or category.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a591124c8190842e7ef18b064198 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f513608190b716b939d574c292 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.