Triple
T32330247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bureau of Corrections |
E826029
|
entity |
| Predicate | typeOfPrisonersHandled |
P102118
|
FINISHED |
| Object | persons convicted by final judgment |
—
|
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: persons convicted by final judgment | Statement: [Bureau of Corrections, typeOfPrisonersHandled, persons convicted by final judgment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfPrisonersHandled Context triple: [Bureau of Corrections, typeOfPrisonersHandled, persons convicted by final judgment]
-
A.
prisonerType
chosen
Indicates the classification or category assigned to a prisoner within a correctional or detention system.
-
B.
prisonType
Indicates the specific category or classification of a prison associated with an entity.
-
C.
numberOfInmatesInvolved
Indicates the count of inmates who participated in or were involved in a specified incident or event.
-
D.
numberOfPrisonersApproximate
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
-
E.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
- 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_69f34913d9048190befaa634025232be |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a004fd3caf48190b2ec063a7bf0756b |
completed | May 10, 2026, 9:28 a.m. |
| PD | Predicate disambiguation | batch_6a004f7672dc8190aca91d1ed855bf9a |
completed | May 10, 2026, 9:27 a.m. |
Created at: May 1, 2026, 12:47 a.m.