Triple
T29409502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supreme Court of Uruguay |
E745854
|
entity |
| Predicate | maximumAgeForJudges |
P32459
|
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: [Supreme Court of Uruguay, maximumAgeForJudges, 70]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumAgeForJudges Context triple: [Supreme Court of Uruguay, maximumAgeForJudges, 70]
-
A.
maximumAgeOfJudges
chosen
Indicates the highest allowable age that individuals may have in order to serve as judges.
-
B.
judgesServeUntil
Indicates that a judge continues to hold and perform their judicial office up to a specified end date or condition.
-
C.
lengthOfJudgeship
Indicates the duration of time that an individual serves or has served in a judicial office or judgeship.
-
D.
numberOfPermanentJudges
Indicates the total count of judges who hold permanent (non-temporary) positions within a given judicial body or court.
-
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_69f0a79eb7d081908c67197a5f347e68 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 28, 2026, 2:56 p.m.