Triple
T10732445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Detention Center, Los Angeles |
E253106
|
entity |
| Predicate | inmateGenderPrimary |
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: [Metropolitan Detention Center, Los Angeles, inmateGenderPrimary, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inmateGenderPrimary Context triple: [Metropolitan Detention Center, Los Angeles, inmateGenderPrimary, male]
-
A.
hasInmateGender
chosen
Indicates that an inmate possesses a specified gender.
-
B.
hasPerpetratorGender
Indicates that an action, event, or offense is associated with the specified gender of the perpetrator.
-
C.
inmateAgeGroup
Indicates the age-range category to which an inmate belongs.
-
D.
genderOfFirstHolder
Indicates that the relationship specifies the gender of the first entity that holds or possesses something in the described context.
-
E.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d7101f35888190b88662372a7d100d |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f309a44881908e49e3ba478c35b4 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:14 p.m.