Triple
T9337657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Correctional Institution El Reno |
E224685
|
entity |
| Predicate | isMaleOnlyFacility |
P32136
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Federal Correctional Institution El Reno, isMaleOnlyFacility, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMaleOnlyFacility Context triple: [Federal Correctional Institution El Reno, isMaleOnlyFacility, true]
-
A.
isSingleSex
chosen
Indicates that the entity involves or is restricted to only one biological sex or gender, rather than being mixed or coeducational.
-
B.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
C.
isMaleOnlyOfficeIn
Indicates that an office or workplace is located in a place where only males are allowed to work or be employed.
-
D.
hasGenderRequirement
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
E.
isGenderSpecificCategory
Indicates that the category applies specifically to one gender rather than being gender-neutral.
- 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_69ca84286fcc81909f6e7fd7a7e862a2 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd37f312408190b5501432a6a855b7 |
completed | April 1, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69cc7a66aef08190b8d668cff5b04f5f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:40 p.m.