Triple

T83605
Position Surface form Disambiguated ID Type / Status
Subject Wuhan E1680 entity
Predicate hasSubdivisions P747 FINISHED
Object 13 districts 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: 13 districts | Statement: [Wuhan, hasSubdivisions, 13 districts]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSubdivisions
Context triple: [Wuhan, hasSubdivisions, 13 districts]
  • A. hasSubdivision chosen
    Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
  • B. countrySubdivision
    Indicates that one geopolitical region is an administrative or territorial subdivision of a larger country.
  • C. hasDivisionLevel
    Indicates that one entity is associated with a specific hierarchical or organizational division level of another entity.
  • D. hasAdministrativeCenter
    Indicates that an administrative unit (such as a region, district, or municipality) has a specific place designated as its main governing or administrative center.
  • E. hasOverseasTerritory
    Indicates that one entity possesses or controls a territory located outside its own primary geographic or sovereign 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_69a24c8150408190910a693eb51c1f71 completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a24f4ccb5081908decac81f4af01bf completed Feb. 28, 2026, 2:13 a.m.
PD Predicate disambiguation batch_69a24eb469548190b38c24e81f36c838 completed Feb. 28, 2026, 2:11 a.m.
Created at: Feb. 28, 2026, 2:06 a.m.