Triple

T20103249
Position Surface form Disambiguated ID Type / Status
Subject Huizhou E496601 entity
Predicate borders P224 FINISHED
Object Dongguan NE NERFINISHED

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: Dongguan | Statement: [Huizhou, borders, Dongguan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dongguan
Context triple: [Huizhou, borders, Dongguan]
  • A. Dongguan chosen
    Dongguan is a major manufacturing and industrial city in Guangdong Province, China, known for its role in the Pearl River Delta economic region.
  • B. Zhongshan
    Zhongshan is an ancient Chinese city historically notable as the capital of the Later Yan state during the Sixteen Kingdoms period.
  • C. Zhongshan
    Zhongshan is a prefecture-level city in Guangdong Province, southern China, known for its manufacturing industry and as the birthplace of revolutionary leader Sun Yat-sen.
  • D. Guangzhou
    Guangzhou is a major port city in southern China and the capital of Guangdong Province, known as a key commercial and manufacturing hub in the Pearl River Delta.
  • E. Zhuhai
    Zhuhai is a coastal city in Guangdong Province, China, known for its proximity to Macau, its role in the Pearl River Delta economic zone, and its reputation as a popular tourist destination.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6667170a4819085d07a4188ded541 completed April 20, 2026, 5:46 p.m.
Created at: April 11, 2026, 11:27 p.m.