Triple

T10851349
Position Surface form Disambiguated ID Type / Status
Subject Prince Gong E256152 entity
Predicate givenName P17 FINISHED
Object Yixin
Yixin, better known as Prince Gong, was a prominent Qing dynasty statesman and imperial prince who played a key role in 19th-century Chinese diplomacy and reform efforts.
 E891687 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: Yixin | Statement: [Prince Gong, givenName, Yixin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yixin
Context triple: [Prince Gong, givenName, Yixin]
  • A. Yuanxin
    Yuanxin is the given name of Mao Yuanxin, a Chinese political figure known for being the nephew of Mao Zedong and a prominent youth leader during the Cultural Revolution.
  • B. Yuxiang
    Yuxiang is a Chinese given name notably borne by the early 20th-century warlord and military leader Feng Yuxiang.
  • C. Xingyuan
    Xingyuan was the Chinese era name used during part of Emperor Dezong of Tang’s reign in the late eighth century.
  • D. Yuanding
    Yuanding was a regnal era of Emperor Wu of the Western Han dynasty in ancient China, used to designate a specific period of his reign.
  • E. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • 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: Yixin
Triple: [Prince Gong, givenName, Yixin]
Generated description
Yixin, better known as Prince Gong, was a prominent Qing dynasty statesman and imperial prince who played a key role in 19th-century Chinese diplomacy and reform efforts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yixin
Target entity description: Yixin, better known as Prince Gong, was a prominent Qing dynasty statesman and imperial prince who played a key role in 19th-century Chinese diplomacy and reform efforts.
  • A. Yuanxin
    Yuanxin is the given name of Mao Yuanxin, a Chinese political figure known for being the nephew of Mao Zedong and a prominent youth leader during the Cultural Revolution.
  • B. Yuxiang
    Yuxiang is a Chinese given name notably borne by the early 20th-century warlord and military leader Feng Yuxiang.
  • C. Xingyuan
    Xingyuan was the Chinese era name used during part of Emperor Dezong of Tang’s reign in the late eighth century.
  • D. Yuanding
    Yuanding was a regnal era of Emperor Wu of the Western Han dynasty in ancient China, used to designate a specific period of his reign.
  • E. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • 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_69e154b2eb08819080a9905dbf378111 completed April 16, 2026, 9:29 p.m.
NEDg Description generation batch_69e174d962ec8190a0ef8442e3414a8d completed April 16, 2026, 11:46 p.m.
NED2 Entity disambiguation (via description) batch_69e1777c0a308190bb5dc5e64cb51af3 completed April 16, 2026, 11:57 p.m.
Created at: April 8, 2026, 9:20 p.m.