Triple

T7795410
Position Surface form Disambiguated ID Type / Status
Subject Sun Wen E180286 entity
Predicate spouse P13 FINISHED
Object Lu Muzhen E182650 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: Lu Muzhen | Statement: [Sun Wen, spouse, Lu Muzhen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lu Muzhen
Context triple: [Sun Wen, spouse, Lu Muzhen]
  • A. Lu Muzhen chosen
    Lu Muzhen was the first wife of Chinese revolutionary leader Sun Yat-sen, known primarily for her connection to his early life and career.
  • B. 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.
  • C. Mao Buyi
    Mao Buyi is a Chinese singer-songwriter known for his introspective lyrics and breakout success after winning the talent show "The Coming One."
  • D. Liu Cunhou
    Liu Cunhou was a Chinese military officer and warlord associated with the Yunnan clique during the early Republican era.
  • E. Liu Bingzhong
    Liu Bingzhong was a prominent Yuan dynasty scholar-official, architect, and urban planner best known for helping design the Mongol capital that became Beijing.
  • 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_69ca827d22208190b4dc5aa680edcf5d completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae93b262c8190b55e5ab2bc72d894 completed March 30, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cbdeb6c1b88190a38fb4507bfb380c completed March 31, 2026, 2:48 p.m.
Created at: March 30, 2026, 4:31 p.m.