Triple
T14079412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oita District Court |
E338824
|
entity |
| Predicate | hearsJuryType |
P13938
|
FINISHED |
| Object | saiban-in lay judge system cases |
—
|
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: saiban-in lay judge system cases | Statement: [Oita District Court, hearsJuryType, saiban-in lay judge system cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hearsJuryType Context triple: [Oita District Court, hearsJuryType, saiban-in lay judge system cases]
-
A.
hasJuryType
chosen
Indicates that an entity is associated with, or classified by, a specific type or category of jury.
-
B.
usesJuries
Indicates that a legal system, court, or process employs juries to participate in deciding cases or determining outcomes.
-
C.
hasJurors
Indicates that one entity serves as or includes jurors in relation to another entity, typically in the context of a legal case or proceeding.
-
D.
hearsCasesAs
Indicates that one judicial body or judge reviews and adjudicates cases originating from another court or jurisdiction.
-
E.
hearsCasesWith
Indicates that one judicial body or judge conducts proceedings together with another judicial body or judge in hearing the same cases.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5e027881908f610f5bab7598d4 |
completed | April 14, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.