Triple

T23243863
Position Surface form Disambiguated ID Type / Status
Subject Xiangcheng County E581529 entity
Predicate hasCategory P87 FINISHED
Object Zhoukou E217755 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: Zhoukou | Statement: [Xiangcheng County, hasCategory, Zhoukou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhoukou
Context triple: [Xiangcheng County, hasCategory, Zhoukou]
  • A. Zhoukou chosen
    Zhoukou is a prefecture-level city in eastern Henan Province, China, known as an important agricultural and transportation hub with historical and cultural significance.
  • B. Zhumadian
    Zhumadian is a prefecture-level city in southern Henan Province, China, known as an important regional transport and agricultural hub.
  • 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. Shangqiu
    Shangqiu is a historic prefecture-level city in eastern Henan Province, China, known as one of the country’s ancient capitals and an important regional transportation hub.
  • 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_69e24606b17c81908aba1a4911c8a8ba completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f192efd44c8190b179b4d1cb71efa5 completed April 29, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c5db7f118819098050e612dd98bef completed May 19, 2026, 12:55 p.m.
Created at: April 17, 2026, 4:10 p.m.