Triple
T29009810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North County Correctional Facility |
E736532
|
entity |
| Predicate | inmateSecurityClassification |
P105493
|
FINISHED |
| Object | medium security |
—
|
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: medium security | Statement: [North County Correctional Facility, inmateSecurityClassification, medium security]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inmateSecurityClassification Context triple: [North County Correctional Facility, inmateSecurityClassification, medium security]
-
A.
securityClassification
Indicates the level or category of security sensitivity or access restriction assigned to an entity.
-
B.
hasInmateCustodyLevel
chosen
Indicates the security or supervision level at which an inmate is held in custody.
-
C.
securityForInmates
Indicates the provision or management of protective measures and safeguards specifically intended for inmates.
-
D.
securityClassificationReason
Indicates the justification or basis for assigning a particular security classification to an entity or information.
-
E.
hasSecurityClass
Indicates that an entity is assigned to or associated with a particular security classification level.
- 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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f65fdb92508190bd0e7fe7877cdae2 |
completed | May 2, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 9:41 a.m.