Triple
T19236184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colorado State Penitentiary |
E481002
|
entity |
| Predicate | hasTypeOfIncarceration |
P19110
|
FINISHED |
| Object | closed custody |
—
|
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: closed custody | Statement: [Colorado State Penitentiary, hasTypeOfIncarceration, closed custody]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfIncarceration Context triple: [Colorado State Penitentiary, hasTypeOfIncarceration, closed custody]
-
A.
prisonType
chosen
Indicates the specific category or classification of a prison associated with an entity.
-
B.
hasPrison
Indicates that one entity possesses, contains, or is the location of a prison associated with another entity.
-
C.
hasInmateCustodyLevel
Indicates the security or supervision level at which an inmate is held in custody.
-
D.
hasBeenImprisoned
Indicates that an entity has been confined or incarcerated in a prison or similar detention facility at some point in time.
-
E.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
- 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_69d8e8ccb8f48190ad420098e74fb1db |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faed9ef0819085035cc17d1546e5 |
completed | April 20, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e4dcfae6f081909cc173cf71a5005c |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:26 p.m.