Triple

T26398331
Position Surface form Disambiguated ID Type / Status
Subject Chinese Jia-A League E663632 entity
Predicate successorFormatChange P180206 FINISHED
Object rebranded and restructured as Chinese Super League 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: rebranded and restructured as Chinese Super League | Statement: [Chinese Jia-A League, successorFormatChange, rebranded and restructured as Chinese Super League]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: successorFormatChange
Context triple: [Chinese Jia-A League, successorFormatChange, rebranded and restructured as Chinese Super League]
  • A. successorSystem
    Indicates that one system directly follows and replaces another in function, role, or version.
  • B. successorModel
    Indicates that one model is the direct follow-up or replacement for another earlier model.
  • C. successorRegimeType
    Indicates the type or form of government or regime that directly follows and replaces a preceding regime.
  • D. successorAgeCategoryChange
    Indicates a change in age category that occurs for an entity’s successor, reflecting a transition from one age group classification to another.
  • E. successorProtocol
    Indicates that one protocol directly follows and replaces another in sequence or versioning.
  • 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_69ee883823988190b418b111be28a44a completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f739a638748190808e7a2930dce16e completed May 3, 2026, 12:03 p.m.
PD Predicate disambiguation batch_69f732f2dc6c8190a4e86da98cc5eb05 completed May 3, 2026, 11:35 a.m.
PDg Predicate description generation batch_69f739a58b3c81908abc2b8738a65678 completed May 3, 2026, 12:03 p.m.
Created at: April 26, 2026, 11:30 p.m.