Triple

T916656
Position Surface form Disambiguated ID Type / Status
Subject Zhang Fakui E19786 entity
Predicate name P16 FINISHED
Object Zhang Fakui E19786 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: Zhang Fakui | Statement: [Zhang Fakui, name, Zhang Fakui]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhang Fakui
Context triple: [Zhang Fakui, name, Zhang Fakui]
  • A. Zhang Fakui chosen
    Zhang Fakui was a prominent Nationalist Chinese general who played key roles in major early battles of the Second Sino-Japanese War.
  • B. Liang Xiaosheng
    Liang Xiaosheng is a prominent Chinese writer and scholar best known for his realist novels depicting ordinary people's lives in contemporary China.
  • C. Sun Lianzhong
    Sun Lianzhong was a Nationalist Chinese general noted for his leadership in key battles against Japanese forces during the Second Sino-Japanese War.
  • D. 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.
  • E. Zhang Jun
    Zhang Jun is a Chinese jurist and senior official who serves as the President and Chief Justice of the Supreme People's Court of 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_69a4939f91a08190ba68c2c81eab90fe completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2f8e26c81908b768d3e9e67689d completed March 1, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac89f641c48190b7cff1073852a228 completed March 7, 2026, 8:26 p.m.
Created at: March 1, 2026, 7:39 p.m.