Triple
T31496440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arizona Justice Courts |
E803553
|
entity |
| Predicate | judicialOfficerType |
P140026
|
FINISHED |
| Object | justice of the peace |
—
|
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: justice of the peace | Statement: [Arizona Justice Courts, judicialOfficerType, justice of the peace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: judicialOfficerType Context triple: [Arizona Justice Courts, judicialOfficerType, justice of the peace]
-
A.
judicialRole
Indicates that one entity holds or performs a specific official function or position within the judicial system in relation to another entity or legal matter.
-
B.
hasJudicialOfficer
Indicates that an entity is associated with or served by a specific judicial officer (such as a judge or magistrate) responsible for legal or court-related functions.
-
C.
courtRole
Indicates the specific capacity or position an entity holds within a court proceeding or judicial context.
-
D.
typeOfJurist
chosen
Indicates that one entity is a specific kind or category of jurist in relation to another entity.
-
E.
courtPerson
Indicates that one person is romantically pursuing or attempting to win the favor of another person.
- 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_69f348cae52081909fa8e5f697523ae3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a1ea029c8190ab83ffdf6a18caf8 |
completed | May 3, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69f69fe82e5c81909da9db0a2f3bba6d |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:41 p.m.