Triple

T680273
Position Surface form Disambiguated ID Type / Status
Subject Jiangsu E13166 entity
Predicate hasMajorCity P316 FINISHED
Object Changzhou E59852 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: Changzhou | Statement: [Jiangsu, hasMajorCity, Changzhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changzhou
Context triple: [Jiangsu, hasMajorCity, Changzhou]
  • A. Changzhou chosen
    Changzhou is a major industrial and commercial city in Jiangsu Province, eastern China, known for its manufacturing base and location along the Yangtze River.
  • B. Wuxi
    Wuxi is a major industrial and cultural city in eastern China, located near Lake Tai and known for its manufacturing, canals, and historic gardens.
  • C. Xuzhou
    Xuzhou is a major historic city in northern Jiangsu Province, China, known as a strategic transportation hub and former battleground in multiple Chinese conflicts.
  • D. Suzhou
    Suzhou is a historic and economically significant city in eastern China, renowned for its classical gardens, canals, and silk industry.
  • E. Nanjing
    Nanjing is a major city in eastern China, historically significant as a former national capital and cultural center, and now an important political, economic, and educational hub on the Yangtze River.
  • 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a04f4efc819082767a7517fa760a completed March 1, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6ef9b97881908eab2a5472b02183 completed March 7, 2026, 6:31 p.m.
Created at: March 1, 2026, 7:36 p.m.