Triple

T4469235
Position Surface form Disambiguated ID Type / Status
Subject Yunnan Military Academy E98453 entity
Predicate notableAlumnus P304 FINISHED
Object Li Jiayu
Li Jiayu was a Chinese military officer and general associated with the National Revolutionary Army during the Republican era.
E488865 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: Li Jiayu | Statement: [Yunnan Military Academy, notableAlumnus, Li Jiayu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Li Jiayu
Context triple: [Yunnan Military Academy, notableAlumnus, Li Jiayu]
  • A. Li Jingxi
    Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
  • B. Zhu Yijun
    Zhu Yijun was the Ming dynasty ruler better known as the Wanli Emperor, whose long reign from 1572 to 1620 saw both early prosperity and later decline of the dynasty.
  • C. Zhu Junyi
    Zhu Junyi is a former senior Chinese police and security official best known for his involvement in major corruption scandals.
  • D. Lin Yurong
    Lin Yurong is the original birth name of Lin Biao, a prominent Chinese Communist military leader and key figure in the Chinese Civil War and early People’s Republic of China.
  • E. Zhu Yawen
    Zhu Yawen is a Chinese actor known for his roles in film and television dramas, particularly in military and historical series.
  • 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: Li Jiayu
Triple: [Yunnan Military Academy, notableAlumnus, Li Jiayu]
Generated description
Li Jiayu was a Chinese military officer and general associated with the National Revolutionary Army during the Republican era.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Li Jiayu
Target entity description: Li Jiayu was a Chinese military officer and general associated with the National Revolutionary Army during the Republican era.
  • A. Li Jingxi
    Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
  • B. Zhu Yijun
    Zhu Yijun was the Ming dynasty ruler better known as the Wanli Emperor, whose long reign from 1572 to 1620 saw both early prosperity and later decline of the dynasty.
  • C. Zhu Junyi
    Zhu Junyi is a former senior Chinese police and security official best known for his involvement in major corruption scandals.
  • D. Lin Yurong
    Lin Yurong is the original birth name of Lin Biao, a prominent Chinese Communist military leader and key figure in the Chinese Civil War and early People’s Republic of China.
  • E. Zhu Yawen
    Zhu Yawen is a Chinese actor known for his roles in film and television dramas, particularly in military and historical series.
  • 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_69b3454b4ae481908967426dd37284d6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3569cd03c8190927c596bedb45ac8 completed March 13, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69be9c31748c81909477e01261b5a78a completed March 21, 2026, 1:25 p.m.
NEDg Description generation batch_69be9e3cfa8081909378c552be3ecb41 completed March 21, 2026, 1:33 p.m.
NED2 Entity disambiguation (via description) batch_69be9e902e3881909f2662cf8f086cd9 completed March 21, 2026, 1:35 p.m.
Created at: March 12, 2026, 11:34 p.m.