Triple
T36128243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vera Bates |
E1044942
|
entity |
| Predicate | relatedLegalEvent |
—
|
GENERATED |
| Object | John Bates’s arrest |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedLegalEvent Context triple: [Vera Bates, relatedLegalEvent, John Bates’s arrest]
-
A.
relatedLegalProcess
chosen
Indicates that there is an associated legal proceeding or action that is connected to, arises from, or is otherwise relevant to the referenced entity or event.
-
B.
legalStatusEvent
Indicates an event or action that changes, establishes, or affects the legal status or standing of an entity.
-
C.
judicialEvent
Indicates a relationship where an event involves judicial or court-related proceedings, such as trials, hearings, or legal rulings.
-
D.
legalCaseRelatedTo
Indicates that there is a relevant connection or association between a legal case and another entity, such as a person, organization, event, or legal matter.
-
E.
associatedCourtCase
Indicates a relationship where one entity is linked to, or involved in, a particular court case.
- F. None of above.
Provenance (1 batch)
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_69f76e356c908190abc6ca1e6a05b011 |
completed | May 3, 2026, 3:48 p.m. |
Created at: May 3, 2026, 4:08 p.m.