Triple

T414072
Position Surface form Disambiguated ID Type / Status
Subject Yangtze River Economic Belt E9552 entity
Predicate includesMajorCity P316 FINISHED
Object Nanjing E29741 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: Nanjing | Statement: [Yangtze River Economic Belt, includesMajorCity, Nanjing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanjing
Context triple: [Yangtze River Economic Belt, includesMajorCity, Nanjing]
  • A. Nanjing chosen
    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.
  • B. 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.
  • 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. Hefei
    Hefei is the capital and largest city of Anhui Province in eastern China, known as a major industrial, scientific, and educational center.
  • E. Shanghai
    Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
  • 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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ee2d6fe481908ff70ab7d043bb3e completed Feb. 28, 2026, 1:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4a424e0d88190b0ad5d0827b762ae completed March 1, 2026, 8:40 p.m.
Created at: Feb. 28, 2026, 1:09 p.m.