Triple
T31826342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broward County Jail system |
E812404
|
entity |
| Predicate | hasSecurityLevels |
P84572
|
FINISHED |
| Object | minimum 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: minimum security | Statement: [Broward County Jail system, hasSecurityLevels, minimum security]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecurityLevels Context triple: [Broward County Jail system, hasSecurityLevels, minimum security]
-
A.
securityLevelsInclude
Indicates that one entity’s defined security levels contain or encompass the security levels of another entity.
-
B.
hasSecretLevel
Indicates that an entity is associated with a particular secrecy or security classification level.
-
C.
hasSecurityDimension
Indicates that something possesses or is associated with a particular aspect or dimension of security.
-
D.
hasSecurityCategory
Indicates that an entity is associated with a particular security classification or category defining its protection or access level.
-
E.
securityLevelDetail
chosen
Indicates the specific classification or degree of security associated with an entity, often including nuanced or descriptive information about its protection 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_69f348e97fa48190aa06286962af6dee |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff2d22ffb48190ae58ddf3c7e02869 |
completed | May 9, 2026, 12:48 p.m. |
| PD | Predicate disambiguation | batch_69ff2ac2e1c4819096cc64e94aef2ff0 |
completed | May 9, 2026, 12:38 p.m. |
Created at: April 30, 2026, 11:46 p.m.