Triple

T17943988
Position Surface form Disambiguated ID Type / Status
Subject Kenli District E448654 entity
Predicate regionalCodeType P3820 FINISHED
Object county-level division code (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: county-level division code (China) | Statement: [Kenli District, regionalCodeType, county-level division code (China)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: regionalCodeType
Context triple: [Kenli District, regionalCodeType, county-level division code (China)]
  • A. regionCodeType chosen
    Indicates the classification or format type used for a given region code within a coding or identification system.
  • B. hasRegionCode
    Indicates that an entity is associated with a specific regional identifier or code.
  • C. typeOfRegionalization
    Indicates the specific method or scheme by which a larger area is divided into regions or regional units.
  • D. regionalType
    Indicates the classification of a region according to its designated type or category within a broader geographic or administrative system.
  • E. ISO3166-2RegionCode
    Indicates the standardized ISO 3166-2 code that specifies the particular primary administrative subdivision (such as a state, province, or region) to which an entity belongs.
  • 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_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4ad9819a88190ad4ea7d562cf3f28 completed April 19, 2026, 10:25 a.m.
PD Predicate disambiguation batch_69e3f8f2bd088190b1e22ad4d9cc8b13 completed April 18, 2026, 9:34 p.m.
Created at: April 10, 2026, 10:21 a.m.