Triple
T996243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George R. Vierno Center |
E21500
|
entity |
| Predicate | typeOfInmates |
P18550
|
FINISHED |
| Object | detainees awaiting trial |
—
|
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: detainees awaiting trial | Statement: [George R. Vierno Center, typeOfInmates, detainees awaiting trial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfInmates Context triple: [George R. Vierno Center, typeOfInmates, detainees awaiting trial]
-
A.
prisonType
Indicates the specific category or classification of a prison associated with an entity.
-
B.
hasNotableCategoryOfPrisoners
chosen
Indicates that a prison is known for housing a specific, notable category or type of prisoners.
-
C.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
-
D.
prisonRole
Indicates a role or function that an entity holds within the context or system of a prison.
-
E.
numberOfPrisonersApproximate
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4df6dcc819084a7c0a50637a2c2 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2af071c819086c374a16307dfe0 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.