Triple
T35626852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division of Adult Correction |
E1029479
|
entity |
| Predicate | hasTypeOfOffenderSupervision |
P195857
|
FINISHED |
| Object | incarceration |
—
|
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: incarceration | Statement: [Division of Adult Correction, hasTypeOfOffenderSupervision, incarceration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfOffenderSupervision Context triple: [Division of Adult Correction, hasTypeOfOffenderSupervision, incarceration]
-
A.
hasSupervisionType
chosen
Indicates the specific kind or category of supervision that one entity exercises over another.
-
B.
targetOffenderType
Indicates the specific category or type of offender that an action, rule, or condition is directed toward.
-
C.
isForConvictedOffenders
Indicates that something is intended to apply to, be used by, or be relevant for individuals who have been legally convicted of offenses.
-
D.
typeOfConvict
Indicates the specific category or classification of a convict in relation to their conviction or legal status.
-
E.
hasCriminalPenalty
Indicates that a specified action, condition, or violation is subject to punishment under criminal law.
- 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_69f76e07bb0c8190968ea2d836fc42c9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff84df768c81908c65a1a7e33103ad |
completed | May 9, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69ff848d0af881908ee42c27a58af47e |
completed | May 9, 2026, 7:01 p.m. |
Created at: May 3, 2026, 4:05 p.m.