Triple

T186417
Position Surface form Disambiguated ID Type / Status
Subject district courts of Japan E3990 entity
Predicate civilPanelComposition P2279 FINISHED
Object usually one professional judge 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: usually one professional judge | Statement: [district courts of Japan, civilPanelComposition, usually one professional judge]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: civilPanelComposition
Context triple: [district courts of Japan, civilPanelComposition, usually one professional judge]
  • A. numberOfJudges chosen
    Indicates the total count of judges associated with a particular case, event, or entity.
  • B. judicialBody
    Indicates that an entity serves as a court or tribunal with authority to adjudicate legal disputes or interpret and apply the law.
  • C. hasCommittee
    Indicates that an entity is associated with or overseen by a specific committee.
  • D. partyRepresentation
    Indicates that one party acts on behalf of, or serves as the representative of, another party in a given context or proceeding.
  • E. chamberInvolved
    Indicates that a particular chamber (e.g., legislative or judicial body) participates in, is affected by, or plays a role in the referenced event, process, or relationship.
  • 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.