Triple
T5403846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisiana Courts of Appeal |
E120842
|
entity |
| Predicate | hasTermLengthForJudges |
P38633
|
FINISHED |
| Object | 10 years |
—
|
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: 10 years | Statement: [Louisiana Courts of Appeal, hasTermLengthForJudges, 10 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTermLengthForJudges Context triple: [Louisiana Courts of Appeal, hasTermLengthForJudges, 10 years]
-
A.
maximumAgeOfJudges
Indicates the highest allowable age that individuals may have in order to serve as judges.
-
B.
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.
-
C.
setJudgeTermLength
chosen
Indicates setting or assigning the duration of a judge’s term of service.
-
D.
lengthOfJudgeship
Indicates the duration of time that an individual serves or has served in a judicial office or judgeship.
-
E.
judgesServeUntil
Indicates that a judge continues to hold and perform their judicial office up to a specified end date or condition.
- 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_69bd46391c0c81909fa484446732b6a3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:04 p.m.