Triple
T27741797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey politics |
E701873
|
entity |
| Predicate | judicialMandatoryRetirementAge |
P2272
|
FINISHED |
| Object | 70 |
—
|
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: 70 | Statement: [New Jersey politics, judicialMandatoryRetirementAge, 70]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: judicialMandatoryRetirementAge Context triple: [New Jersey politics, judicialMandatoryRetirementAge, 70]
-
A.
maximumAgeOfJudges
Indicates the highest allowable age that individuals may have in order to serve as judges.
-
B.
minimumJurorAge
Indicates the minimum age requirement that an individual must meet to be eligible to serve as a juror.
-
C.
mandatoryRetirementAge
chosen
Indicates the age at which an individual is required by rule or policy to retire from a position or role.
-
D.
hasLifeTenureJudges
Indicates that the judges associated with an office, position, or institution hold their roles for life, typically remaining in office until they choose to retire, resign, or are removed under exceptional circumstances.
-
E.
hasSeniorJudge
Indicates that one entity is assigned or linked to another entity serving in the role of a senior judge.
- 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f637169d6c8190bf74d5b882d2eb7d |
completed | May 2, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69f63188e7408190af8ce8b93d128c63 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 4:11 p.m.