Triple

T10851301
Position Surface form Disambiguated ID Type / Status
Subject Zeng Guofan E256151 entity
Predicate courtesyName P570 FINISHED
Object Zicheng
Zicheng is the courtesy name of Zeng Guofan, a prominent Qing dynasty statesman, military leader, and Confucian scholar who played a key role in suppressing the Taiping Rebellion.
 E888807 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: Zicheng | Statement: [Zeng Guofan, courtesyName, Zicheng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zicheng
Context triple: [Zeng Guofan, courtesyName, Zicheng]
  • A. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • B. Licheng
    Licheng is the courtesy name of the Daoguang Emperor, a Qing dynasty ruler of China in the early 19th century.
  • C. Yongcheng
    Yongcheng was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor of China.
  • D. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • E. Zhongping
    Zhongping was an era name used during the later years of Emperor Ling’s rule in the Eastern Han dynasty of China.
  • 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: Zicheng
Triple: [Zeng Guofan, courtesyName, Zicheng]
Generated description
Zicheng is the courtesy name of Zeng Guofan, a prominent Qing dynasty statesman, military leader, and Confucian scholar who played a key role in suppressing the Taiping Rebellion.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zicheng
Target entity description: Zicheng is the courtesy name of Zeng Guofan, a prominent Qing dynasty statesman, military leader, and Confucian scholar who played a key role in suppressing the Taiping Rebellion.
  • A. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • B. Licheng
    Licheng is the courtesy name of the Daoguang Emperor, a Qing dynasty ruler of China in the early 19th century.
  • C. Yongcheng
    Yongcheng was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor of China.
  • D. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • E. Zhongping
    Zhongping was an era name used during the later years of Emperor Ling’s rule in the Eastern Han dynasty of China.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75116af20819084c7f8fa88d18e61 completed April 9, 2026, 7:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb17d978c8190883b4a56e88859de completed April 14, 2026, 9:28 p.m.
NEDg Description generation batch_69deb515ab608190981689bcad4b7530 completed April 14, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_69deb602fa908190bffdd291932da3f1 completed April 14, 2026, 9:47 p.m.
Created at: April 8, 2026, 9:20 p.m.