Triple
T722076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werl Prison |
E14637
|
entity |
| Predicate | hasSecondaryPurpose |
P3579
|
FINISHED |
| Object | social reintegration of offenders |
—
|
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: social reintegration of offenders | Statement: [Werl Prison, hasSecondaryPurpose, social reintegration of offenders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryPurpose Context triple: [Werl Prison, hasSecondaryPurpose, social reintegration of offenders]
-
A.
hasPrimaryGoal
Indicates that an entity’s main or most important objective is the specified goal.
-
B.
secondaryFunction
Indicates that an entity has an additional, supporting role or purpose beyond its primary function.
-
C.
secondaryGoal
chosen
Indicates that something serves as a subordinate or supporting objective in addition to a primary goal.
-
D.
hasPrimaryFunction
Indicates that one entity serves as the main or principal function or role of another entity.
-
E.
hasSecondaryMeeting
Indicates that an entity is associated with an additional, follow-up, or subordinate meeting beyond a primary one.
- 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.