Triple

T4293520
Position Surface form Disambiguated ID Type / Status
Subject Zhu E99651 entity
Predicate hasNotableBearer P458 FINISHED
Object Zhu Qinan
Zhu Qinan is a Chinese sport shooter and Olympic gold medalist known for his achievements in the 10 metre air rifle event.
E450536 NE FINISHED

How this triple was built (4 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: Zhu Qinan | Statement: [Zhu, hasNotableBearer, Zhu Qinan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhu Qinan
Context triple: [Zhu, hasNotableBearer, Zhu Qinan]
  • A. Zhu Zhanyong
    Zhu Zhanyong was a Ming dynasty imperial prince, known primarily as a son of the Hongxi Emperor of China.
  • B. Zhang Wenqi
    Zhang Wenqi is a Chinese basketball player best known for having played professionally for the Shanghai Sharks in the Chinese Basketball Association.
  • C. Zhu Chen
    Zhu Chen is a Chinese-born Qatari chess grandmaster and former Women's World Chess Champion.
  • D. Zhu Youyuan
    Zhu Youyuan was a Ming dynasty prince whose posthumous elevation to emperor came only after his son, the Jiajing Emperor, ascended the throne and fought to honor him as an imperial ancestor.
  • E. Peng Sanyuan
    Peng Sanyuan is a Chinese film and television director and screenwriter best known for socially conscious dramas such as the film "Lost and Love."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zhu Qinan
Triple: [Zhu, hasNotableBearer, Zhu Qinan]
Generated description
Zhu Qinan is a Chinese sport shooter and Olympic gold medalist known for his achievements in the 10 metre air rifle event.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zhu Qinan
Target entity description: Zhu Qinan is a Chinese sport shooter and Olympic gold medalist known for his achievements in the 10 metre air rifle event.
  • A. Zhu Zhanyong
    Zhu Zhanyong was a Ming dynasty imperial prince, known primarily as a son of the Hongxi Emperor of China.
  • B. Zhang Wenqi
    Zhang Wenqi is a Chinese basketball player best known for having played professionally for the Shanghai Sharks in the Chinese Basketball Association.
  • C. Zhu Chen
    Zhu Chen is a Chinese-born Qatari chess grandmaster and former Women's World Chess Champion.
  • D. Zhu Youyuan
    Zhu Youyuan was a Ming dynasty prince whose posthumous elevation to emperor came only after his son, the Jiajing Emperor, ascended the throne and fought to honor him as an imperial ancestor.
  • E. Peng Sanyuan
    Peng Sanyuan is a Chinese film and television director and screenwriter best known for socially conscious dramas such as the film "Lost and Love."
  • F. None of above. chosen

Provenance (5 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_69b3455175088190aa79c6e03b86647e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35082228081908504e3fd7c4ca1e8 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdacc9ef8c81909ff2a16cf68844d0 completed March 20, 2026, 8:23 p.m.
NEDg Description generation batch_69bdad757394819091d334c12b660b95 completed March 20, 2026, 8:26 p.m.
NED2 Entity disambiguation (via description) batch_69bdadd612a48190b088fe6ac894dbb5 completed March 20, 2026, 8:28 p.m.
Created at: March 12, 2026, 11:08 p.m.