Triple

T4825708
Position Surface form Disambiguated ID Type / Status
Subject Suzhou E107819 entity
Predicate hasAdministrativeDivision P747 FINISHED
Object Changshu E378831 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: Changshu | Statement: [Suzhou, hasAdministrativeDivision, Changshu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changshu
Context triple: [Suzhou, hasAdministrativeDivision, Changshu]
  • A. Changshu chosen
    Changshu is a county-level city in Jiangsu Province, eastern China, known for its textile industry, historic sites, and location near Suzhou and Shanghai.
  • B. Kunshan
    Kunshan is a rapidly developing county-level city in Jiangsu Province, China, known for its strong manufacturing economy and proximity to Shanghai and Suzhou.
  • C. Changzhou
    Changzhou is a major industrial and commercial city in Jiangsu Province, eastern China, known for its manufacturing base and location along the Yangtze River.
  • D. Zhenjiang
    Zhenjiang is a historic port city in eastern China known for its strategic location on the Yangtze River and its rich cultural and culinary heritage.
  • E. Nantong
    Nantong is a coastal city in eastern China known for its textile industry, river and sea ports, and location on the northern bank of the Yangtze River opposite Shanghai.
  • 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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6caf22308190a2048ec6acfa5af2 completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fa6479c8190b04c2ff50b98ad1d completed March 21, 2026, 10:15 a.m.
Created at: March 20, 2026, 1:24 p.m.