Triple
T8481832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oregon State Penitentiary |
E200536
|
entity |
| Predicate | hasNotableInmateCategory |
P18550
|
FINISHED |
| Object | death row inmates |
—
|
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: death row inmates | Statement: [Oregon State Penitentiary, hasNotableInmateCategory, death row inmates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableInmateCategory Context triple: [Oregon State Penitentiary, hasNotableInmateCategory, death row inmates]
-
A.
hasNotableCategoryOfPrisoners
chosen
Indicates that a prison is known for housing a specific, notable category or type of prisoners.
-
B.
hasPrisonerCategory
Indicates the classification or category assigned to a prisoner within a correctional or detention system.
-
C.
notablePrisoner
Indicates that a person is recognized as a significant or noteworthy inmate of a particular prison or detention facility.
-
D.
hasPrisoners
Indicates that an entity holds or contains one or more individuals who are imprisoned or detained.
-
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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53638c48190b742fc51d1b4442a |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd104250c8190b4c499dcc9937494 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:12 p.m.