Triple

T7824725
Position Surface form Disambiguated ID Type / Status
Subject Shu Han E181217 entity
Predicate eraName P2938 FINISHED
Object Zhangwu
Zhangwu was a historical Chinese era name used during the Three Kingdoms period, specifically associated with the Shu Han state.
 E695251 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: Zhangwu | Statement: [Shu Han, eraName, Zhangwu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zhangwu
Context triple: [Shu Han, eraName, Zhangwu]
  • A. Luzhi
    Luzhi is an ancient canal town near Suzhou in China, renowned for its well-preserved waterways, stone bridges, and traditional Jiangnan architecture.
  • B. Ruchang
    Ruchang is a Chinese given name most notably borne by Ding Ruchang, a late Qing dynasty naval commander.
  • C. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • D. Wuyuan
    Wuyuan is a historic county in northeastern Jiangxi, China, famed for its well-preserved Huizhou-style architecture and picturesque rural landscapes.
  • E. Jinyang
    Jinyang is the historical name of the city now known as Taiyuan, a major urban and industrial center in northern China’s Shanxi province.
  • 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: Zhangwu
Triple: [Shu Han, eraName, Zhangwu]
Generated description
Zhangwu was a historical Chinese era name used during the Three Kingdoms period, specifically associated with the Shu Han state.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zhangwu
Target entity description: Zhangwu was a historical Chinese era name used during the Three Kingdoms period, specifically associated with the Shu Han state.
  • A. Luzhi
    Luzhi is an ancient canal town near Suzhou in China, renowned for its well-preserved waterways, stone bridges, and traditional Jiangnan architecture.
  • B. Ruchang
    Ruchang is a Chinese given name most notably borne by Ding Ruchang, a late Qing dynasty naval commander.
  • C. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • D. Wuyuan
    Wuyuan is a historic county in northeastern Jiangxi, China, famed for its well-preserved Huizhou-style architecture and picturesque rural landscapes.
  • E. Jinyang
    Jinyang is the historical name of the city now known as Taiyuan, a major urban and industrial center in northern China’s Shanxi province.
  • 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_69ca8282ccec819083c48efb72d21cf9 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cafa0c1f5c8190b16db20daad159a1 completed March 30, 2026, 10:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb14aefd4881908ffa5825f4ba6eff completed March 31, 2026, 12:26 a.m.
NEDg Description generation batch_69cb1734159881909590ed51e8920387 completed March 31, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_69cb1a6fc16c8190827593f58b9d742d completed March 31, 2026, 12:50 a.m.
Created at: March 30, 2026, 4:42 p.m.