Triple

T3644448
Position Surface form Disambiguated ID Type / Status
Subject China National Highway 106 E77263 entity
Predicate passesThroughCity P416 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: [China National Highway 106, passesThroughCity, Zhengzhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhengzhou
Context triple: [China National Highway 106, passesThroughCity, 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. Zhoukou
    Zhoukou is a prefecture-level city in eastern Henan Province, China, known as an important agricultural and transportation hub with historical and cultural significance.
  • C. Xuchang
    Xuchang is a historically significant city in central China, known as a former capital during the Three Kingdoms period and now an important industrial and transportation hub.
  • D. Xinxiang
    Xinxiang is a prefecture-level industrial and transportation hub city located in northern Henan Province, China.
  • E. Luoyang
    Luoyang is one of China’s oldest and most historically significant cities, renowned as an ancient imperial capital and cultural center along the Yellow 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_69ad85de1b988190a45f8dbfebc806fc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc35c28908190b253f4835918a2b4 completed March 8, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c38f989c8190befc64db51041a53 completed March 14, 2026, 2:10 a.m.
Created at: March 8, 2026, 3:24 p.m.