Triple

T15692556
Position Surface form Disambiguated ID Type / Status
Subject Li Zicheng E380368 entity
Predicate alternativeName P39 FINISHED
Object Dashun Wang
Dashun Wang is another name for Li Zicheng, the 17th-century Chinese rebel leader who overthrew the Ming dynasty and briefly ruled as emperor of the Shun regime.
 E1172347 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: Dashun Wang | Statement: [Li Zicheng, alternativeName, Dashun Wang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dashun Wang
Context triple: [Li Zicheng, alternativeName, Dashun Wang]
  • A. Yanluo Wang
    Yanluo Wang is the Chinese deity who presides over the underworld and judges the souls of the dead.
  • B. Jin Wang
    Jin Wang is the Chinese American teenage protagonist of Gene Luen Yang’s graphic novel "American Born Chinese," whose story explores identity, assimilation, and cultural conflict.
  • C. Ziyu Wang
    Ziyu Wang is a machine learning researcher best known for co-developing the dueling deep Q-network (Dueling DQN) architecture in deep reinforcement learning.
  • D. Yuhuai Wu
    Yuhuai Wu is an AI researcher and entrepreneur known for his work on large language models and as a member of Elon Musk’s xAI team.
  • E. Xindong Wu
    Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
  • 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: Dashun Wang
Triple: [Li Zicheng, alternativeName, Dashun Wang]
Generated description
Dashun Wang is another name for Li Zicheng, the 17th-century Chinese rebel leader who overthrew the Ming dynasty and briefly ruled as emperor of the Shun regime.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dashun Wang
Target entity description: Dashun Wang is another name for Li Zicheng, the 17th-century Chinese rebel leader who overthrew the Ming dynasty and briefly ruled as emperor of the Shun regime.
  • A. Yanluo Wang
    Yanluo Wang is the Chinese deity who presides over the underworld and judges the souls of the dead.
  • B. Jin Wang
    Jin Wang is the Chinese American teenage protagonist of Gene Luen Yang’s graphic novel "American Born Chinese," whose story explores identity, assimilation, and cultural conflict.
  • C. Ziyu Wang
    Ziyu Wang is a machine learning researcher best known for co-developing the dueling deep Q-network (Dueling DQN) architecture in deep reinforcement learning.
  • D. Yuhuai Wu
    Yuhuai Wu is an AI researcher and entrepreneur known for his work on large language models and as a member of Elon Musk’s xAI team.
  • E. Xindong Wu
    Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4f5a888190bd3681bcb9bbc02f completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff7571f1888190b83af75ec9c7432b completed May 9, 2026, 5:57 p.m.
NEDg Description generation batch_69ff76cdbddc81908c7350473195cdac completed May 9, 2026, 6:02 p.m.
NED2 Entity disambiguation (via description) batch_69ff77ab82d08190a3e6b08fd57587a3 completed May 9, 2026, 6:06 p.m.
Created at: April 10, 2026, 4:44 a.m.