Triple

T775367
Position Surface form Disambiguated ID Type / Status
Subject Yellow River E16374 entity
Predicate majorCityOnRiver P316 FINISHED
Object Zhengzhou E125528 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: Zhengzhou | Statement: [Yellow River, majorCityOnRiver, Zhengzhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhengzhou
Context triple: [Yellow River, majorCityOnRiver, Zhengzhou]
  • A. Zhengzhou chosen
    Zhengzhou is a major city in central China that serves as the capital of Henan Province and an important national transportation and industrial hub.
  • B. Kaifeng
    Kaifeng is an ancient city in eastern Henan, China, historically significant as a former capital of several Chinese dynasties and a major cultural and economic center.
  • C. Anyang
    Anyang is an ancient city in northern China renowned as one of the historical capitals of the Shang dynasty and a major archaeological site.
  • D. Xiangyang
    Xiangyang is a historic prefecture-level city in northern Hubei Province, China, known for its strategic location on the Han River and well-preserved ancient city walls.
  • E. Wuhan
    Wuhan is a major city in central China, known as a key industrial, commercial, and transportation hub located at the confluence of the Yangtze and Han rivers.
  • 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_69a49369a0848190af883934cee3db4c completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a73236288190b82d66202f2f7399 completed March 1, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce4e94688190bc29b4a1e26f6b93 completed March 8, 2026, 1:18 a.m.
Created at: March 1, 2026, 7:37 p.m.