Triple
T25424415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Correctional Institution, Ray Brook |
E637079
|
entity |
| Predicate | inmateGenderOfPrisonCamp |
P81519
|
FINISHED |
| Object | male |
—
|
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: male | Statement: [Federal Correctional Institution, Ray Brook, inmateGenderOfPrisonCamp, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inmateGenderOfPrisonCamp Context triple: [Federal Correctional Institution, Ray Brook, inmateGenderOfPrisonCamp, male]
-
A.
hasInmateGender
chosen
Indicates that an inmate possesses a specified gender.
-
B.
prisonType
Indicates the specific category or classification of a prison associated with an entity.
-
C.
prisonerType
Indicates the classification or category assigned to a prisoner within a correctional or detention system.
-
D.
hasNotableCategoryOfPrisoners
Indicates that a prison is known for housing a specific, notable category or type of prisoners.
-
E.
prisonerNumber
Indicates that an entity is assigned a specific identification number used to uniquely identify them as a prisoner.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6bf25c881909f049d5393927bfb |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:57 p.m.