Triple

T16471986
Position Surface form Disambiguated ID Type / Status
Subject 李讷 E400084 entity
Predicate relative P37 FINISHED
Object 毛岸青 E16414 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: 毛岸青 | Statement: [李讷, relative, 毛岸青]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 毛岸青
Context triple: [李讷, relative, 毛岸青]
  • A. 李讷
    李讷 is a Chinese writer and editor best known as the daughter of Mao Zedong and his fourth wife Jiang Qing.
  • B. 宋庆龄
    宋庆龄 was a prominent Chinese revolutionary and political leader, wife of Sun Yat-sen, and later one of the vice chairpersons and honorary presidents of the People’s Republic of China.
  • C. 周恩来
    周恩来是中华人民共和国的开国总理和重要外交家，被视为中国现代史上最具影响力的政治家之一。
  • D. 叶剑英
    叶剑英 was a prominent Chinese Communist military leader and statesman who served as one of the Ten Marshals of the People’s Republic of China and later as its top legislator.
  • E. Mao Anqing chosen
    Mao Anqing was the second son of Chinese Communist leader Mao Zedong, known for his work as a Russian-language translator and his relatively low political profile compared to his father.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32dd19df881909e4562a5e8473338 completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f5d16008190bd874080e86b8a2f completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:11 a.m.