Triple
T36258869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellsworth Correctional Facility |
E892023
|
entity |
| Predicate | hasInmateWorkProgram |
P87760
|
FINISHED |
| Object | prison industries |
—
|
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: prison industries | Statement: [Ellsworth Correctional Facility, hasInmateWorkProgram, prison industries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInmateWorkProgram Context triple: [Ellsworth Correctional Facility, hasInmateWorkProgram, prison industries]
-
A.
hasInmatePrograms
Indicates that an entity provides, offers, or is associated with specific programs or services intended for inmates.
-
B.
hasInmateLabor
Indicates that an entity utilizes or is associated with labor performed by incarcerated individuals.
-
C.
hasWorkProgram
chosen
Indicates that an entity offers, participates in, or is associated with a specific work-related program or scheme.
-
D.
hasPrisonService
Indicates that an entity provides, manages, or is responsible for prison-related services or operations for another entity.
-
E.
hasPrison
Indicates that one entity possesses, contains, or is the location of a prison associated with another entity.
- 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_69f76e4699188190af045b11a840ce31 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a00ada2903481908b28ce55ef97a6c2 |
completed | May 10, 2026, 4:09 p.m. |
| PD | Predicate disambiguation | batch_6a00ad5d23788190b3f9e2de761d39bb |
completed | May 10, 2026, 4:07 p.m. |
Created at: May 3, 2026, 4:09 p.m.