Triple

T4008060
Position Surface form Disambiguated ID Type / Status
Subject Seventh Circuit Court in Xianyang E89574 entity
Predicate handlesCasesFor P16126 FINISHED
Object designated area of western China 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: designated area of western China | Statement: [Seventh Circuit Court in Xianyang, handlesCasesFor, designated area of western China]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: handlesCasesFor
Context triple: [Seventh Circuit Court in Xianyang, handlesCasesFor, designated area of western China]
  • A. hasCase
    Indicates that one entity is involved in, associated with, or characterized by a particular case, instance, or occurrence represented by another entity.
  • B. typeOfCasesHandled
    Indicates the categories or kinds of cases that an entity (such as a person, organization, or system) is responsible for managing or processing.
  • C. canHandle
    Indicates that an entity has the ability or capacity to manage, process, or deal with another entity or situation.
  • D. hearsCasesUnder chosen
    Indicates that a judicial body or authority has the responsibility and power to adjudicate legal cases falling within a specified jurisdiction, category, or scope.
  • E. numberOfCases
    Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
  • 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_69aed9585e788190bec2d39deba3750f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefaec08dc8190a341809059554f84 completed March 9, 2026, 4:53 p.m.
PD Predicate disambiguation batch_69aef8fa6fec81909b1190ecbba61410 completed March 9, 2026, 4:44 p.m.
Created at: March 9, 2026, 3:34 p.m.