Triple

T30716204
Position Surface form Disambiguated ID Type / Status
Subject Chinese military logistics system E782028 entity
Predicate reformFeature P4888 FINISHED
Object creation of Joint Logistic Support Force 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: creation of Joint Logistic Support Force | Statement: [Chinese military logistics system, reformFeature, creation of Joint Logistic Support Force]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: reformFeature
Context triple: [Chinese military logistics system, reformFeature, creation of Joint Logistic Support Force]
  • A. reform chosen
    Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
  • B. reformsBy
    Indicates that one entity initiates, implements, or is responsible for changes or improvements (reforms) affecting another entity.
  • C. featureChange
    Indicates a modification in the properties, characteristics, or attributes of an entity between two states or points in time.
  • D. subjectToReformBy
    Indicates that an entity is undergoing or designated for changes, improvements, or restructuring carried out by another entity.
  • E. reformsArea
    Indicates that an entity is responsible for changing, improving, or restructuring a particular area or domain.
  • 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_69f224acd24481908ed5f96f0d69b5dd completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68c5343b8819082ded39e2e8ee1c8 completed May 2, 2026, 11:44 p.m.
PD Predicate disambiguation batch_69f6861170d08190bb98be609d436f84 completed May 2, 2026, 11:17 p.m.
Created at: April 29, 2026, 8:35 p.m.