Triple

T3917704
Position Surface form Disambiguated ID Type / Status
Subject Li Na E88883 entity
Predicate sibling P363 FINISHED
Object Mao Anlong E105098 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: Mao Anlong | Statement: [Li Na, sibling, Mao Anlong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mao Anlong
Context triple: [Li Na, sibling, Mao Anlong]
  • A. Mao Anlong chosen
    Mao Anlong was one of Mao Zedong’s sons, who died in childhood and is less documented than his more politically prominent siblings.
  • B. Mao Anqing
    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.
  • C. Mao Yuanxin
    Mao Yuanxin is a Chinese political figure known as Mao Zedong’s nephew who briefly held influential positions during the final years of the Cultural Revolution.
  • D. Lu Muzhen
    Lu Muzhen was the first wife of Chinese revolutionary leader Sun Yat-sen, known primarily for her connection to his early life and career.
  • E. Mao Anying
    Mao Anying was the eldest son of Chinese leader Mao Zedong, best known for his death while serving as a volunteer officer in the Korean War.
  • 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_69aed955229881909e85e73ffab1d343 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed5797508190adaddb84575d9bb3 completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b53fefa46c8190a6a2e7d9e90d11dd completed March 14, 2026, 11:01 a.m.
Created at: March 9, 2026, 3:22 p.m.