Triple

T3738801
Position Surface form Disambiguated ID Type / Status
Subject Evergrande Group E79649 entity
Predicate headquartersLocation P62 FINISHED
Object Shenzhen E18299 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: Shenzhen | Statement: [Evergrande Group, headquartersLocation, Shenzhen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shenzhen
Context triple: [Evergrande Group, headquartersLocation, Shenzhen]
  • A. Dongguan
    Dongguan is a major manufacturing and industrial city in Guangdong Province, China, known for its role in the Pearl River Delta economic region.
  • B. 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.
  • C. 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.
  • D. Shenzhen, China chosen
    Shenzhen, China is a major southern Chinese metropolis known for its rapid transformation into a global technology and manufacturing hub bordering Hong Kong.
  • E. 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.
  • 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_69ad8b115610819095b02007da5ca3cb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb404b908190b6b4ee583dee3cc9 completed March 8, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5560a42688190b30bce9b7af10db4 completed March 14, 2026, 12:35 p.m.
Created at: March 8, 2026, 3:34 p.m.