Triple

T8882119
Position Surface form Disambiguated ID Type / Status
Subject Guangxi Clique E211435 entity
Predicate hasLeader P981 FINISHED
Object Huang Shaoxiong E509931 NE FINISHED

How this triple was built (2 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: Huang Shaoxiong | Statement: [Guangxi Clique, hasLeader, Huang Shaoxiong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huang Shaoxiong
Context triple: [Guangxi Clique, hasLeader, Huang Shaoxiong]
  • A. Huang Xingguo
    Huang Xingguo is a Chinese politician who served as acting mayor and then mayor of Tianjin before being investigated and convicted on corruption charges.
  • B. Huang Jianxin
    Huang Jianxin is a prominent Chinese filmmaker known for his socially conscious, often satirical films that explore contemporary Chinese life and politics.
  • C. Huang Shaohong chosen
    Huang Shaohong was a prominent Chinese Nationalist military and political leader who played a key role in the development and governance of Guangxi during the Republican era.
  • D. Huang Xiansheng
    Huang Xiansheng was a Chinese military figure and graduate of the Yunnan Military Academy, an institution known for training many influential officers in modern Chinese history.
  • E. Huang Zhiyong
    Huang Zhiyong was a Chinese military officer and notable graduate of the Yunnan Military Academy who participated in early 20th-century military and political affairs in China.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca838f9e20819096ab1f236a70381a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc616a01f48190b8bbde0e898a38c7 completed April 1, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d181fc06c48190b6a7444d975b1e09 completed April 4, 2026, 9:26 p.m.
Created at: March 30, 2026, 6:53 p.m.