Triple

T7726368
Position Surface form Disambiguated ID Type / Status
Subject Peking opera E175140 entity
Predicate hasRoleType P5518 FINISHED
Object Sheng
Sheng is the primary male role type in traditional Chinese Peking opera, typically portraying dignified scholars, officials, and heroic figures.
 E685460 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: Sheng | Statement: [Peking opera, hasRoleType, Sheng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sheng
Context triple: [Peking opera, hasRoleType, Sheng]
  • A. Shengzhi
    Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
  • B. Shuheng
    Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
  • C. Xuan
    Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
  • D. Ching
    Ching is the surname of Brian Ching, a retired American soccer player best known as a forward for the Houston Dynamo and the U.S. national team.
  • E. Zeng
    Zeng is a Chinese surname and given name commonly rendered in pinyin and borne by numerous historical and contemporary figures in 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: Sheng
Triple: [Peking opera, hasRoleType, Sheng]
Generated description
Sheng is the primary male role type in traditional Chinese Peking opera, typically portraying dignified scholars, officials, and heroic figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sheng
Target entity description: Sheng is the primary male role type in traditional Chinese Peking opera, typically portraying dignified scholars, officials, and heroic figures.
  • A. Shengzhi
    Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
  • B. Shuheng
    Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
  • C. Xuan
    Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
  • D. Ching
    Ching is the surname of Brian Ching, a retired American soccer player best known as a forward for the Houston Dynamo and the U.S. national team.
  • E. Zeng
    Zeng is a Chinese surname and given name commonly rendered in pinyin and borne by numerous historical and contemporary figures in 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_69c6995d541c81909eaa646b1a8369a9 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70314abb88190a7eaa519bd7398c9 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be2de08881909715d9164b743aae completed March 29, 2026, 5:52 a.m.
NEDg Description generation batch_69c8bef91cf081908d9d9c689c918905 completed March 29, 2026, 5:56 a.m.
NED2 Entity disambiguation (via description) batch_69c8bf5aa1348190a5c369bece6fb6db completed March 29, 2026, 5:57 a.m.
Created at: March 27, 2026, 4:05 p.m.