Triple

T16823001
Position Surface form Disambiguated ID Type / Status
Subject Zhu Shizhen E408941 entity
Predicate associatedPlace P1481 FINISHED
Object Haozhou E383465 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: Haozhou | Statement: [Zhu Shizhen, associatedPlace, Haozhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haozhou
Context triple: [Zhu Shizhen, associatedPlace, Haozhou]
  • A. Haozhou chosen
    Haozhou is a historical city in China, known as the birthplace of the Hongwu Emperor, founder of the Ming dynasty.
  • B. Lianzhou
    Lianzhou is a town-level settlement located within Doumen District of Zhuhai in Guangdong Province, China.
  • C. Qingyuan
    Qingyuan is a prefecture-level city in northern Guangdong Province, China, known for its karst landscapes, hot springs, and role as a regional transport hub near the Pearl River Delta.
  • D. Zhishun
    Zhishun was a short-lived era name used during the Yuan dynasty in China.
  • E. Shanwei
    Shanwei is a coastal city in eastern Guangdong Province, China, known for its fishing industry and location along major transportation routes on the South China Sea.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b2e838e881908b650194c9b94886 completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb11f8708190ae762a28710e4246 completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:23 a.m.