Triple

T1643371
Position Surface form Disambiguated ID Type / Status
Subject Kazan E35521 entity
Predicate hasSisterCity P919 FINISHED
Object Guangzhou E5203 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: Guangzhou | Statement: [Kazan, hasSisterCity, Guangzhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guangzhou
Context triple: [Kazan, hasSisterCity, Guangzhou]
  • A. Guangzhou chosen
    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.
  • 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. 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. Port of Guangzhou
    The Port of Guangzhou is one of China’s largest and busiest seaports, serving as a major hub for international trade and shipping in the Pearl River Delta region.
  • 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 (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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a3f4d8c8190aa0a44d1c9b1a7f0 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b4b974081908da05bc63f923215 completed March 9, 2026, 8:19 p.m.
Created at: March 4, 2026, 7:28 p.m.