Triple

T9164399
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou metropolitan area E219910 entity
Predicate includesCity P3207 FINISHED
Object Zhongshan E217727 NE 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: Zhongshan | Statement: [Guangzhou metropolitan area, includesCity, Zhongshan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhongshan
Context triple: [Guangzhou metropolitan area, includesCity, Zhongshan]
  • A. Zhongshan chosen
    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.
  • B. Dongguan
    Dongguan is a major manufacturing and industrial city in Guangdong Province, China, known for its role in the Pearl River Delta economic region.
  • C. 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.
  • D. Foshan
    Foshan is a major industrial and cultural city in southern China known for its manufacturing, Cantonese opera, and martial arts heritage.
  • E. Heyuan
    Heyuan is a prefecture-level city in northeastern Guangdong Province, China, known for its Hakka culture, abundant natural scenery, and large reservoir and river systems.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca83e3633c81908688a9fa2306ba99 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccaa2ee64c8190a9a5abafe5d0b086 completed April 1, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e4d5f5008190a897b3b10b172592 completed April 5, 2026, 10:40 p.m.
Created at: March 30, 2026, 7:21 p.m.