Triple
T186415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district courts of Japan |
E3990
|
entity |
| Predicate | mayUse |
P273
|
FINISHED |
| Object | lay judges in saiban-in system |
—
|
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: lay judges in saiban-in system | Statement: [district courts of Japan, mayUse, lay judges in saiban-in system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayUse Context triple: [district courts of Japan, mayUse, lay judges in saiban-in system]
-
A.
canBe
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
-
B.
allows
chosen
Indicates that one entity grants permission, capability, or opportunity for another entity to perform an action or be in a certain state.
-
C.
regulatesUse
Indicates that one entity controls, governs, or sets rules for how another entity may be used.
-
D.
canEnforce
Indicates that one entity has the authority or capability to compel compliance with rules, decisions, or obligations upon another entity.
-
E.
mayExtendTo
Indicates that something has the potential or permission to reach, continue, or be applied up to a specified limit, scope, or boundary.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594809288190b3d3b1283e7e0d00 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25670feb081908e26a2543ebe7b3a |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.