Triple
T434556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States district courts |
E9783
|
entity |
| Predicate | judgeTerm |
P13936
|
FINISHED |
| Object | life tenure during good behavior for Article III district judges |
—
|
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: life tenure during good behavior for Article III district judges | Statement: [United States district courts, judgeTerm, life tenure during good behavior for Article III district judges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: judgeTerm Context triple: [United States district courts, judgeTerm, life tenure during good behavior for Article III district judges]
-
A.
judge
Indicates that one entity evaluates, forms an opinion about, or makes a decision regarding another entity or situation.
-
B.
judgesTerm
Indicates that one entity formally evaluates or makes a judgment about a specific term or expression.
-
C.
verdict
Indicates the formal decision or judgment reached and declared at the conclusion of a legal or evaluative process.
-
D.
hasJudgeType
Indicates that an entity is associated with a specific category or type of judge.
-
E.
decisionLanguage
Indicates that a decision, statement, or choice is expressed or recorded in a particular natural language.
- F. None of above. chosen
Provenance (4 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ef0a008c8190ae0aa25e4df9c35f |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2edda55e88190b7c17ba94d7df1ce |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb93584819082f23eff13e17c4f |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.