Triple

T12661547
Position Surface form Disambiguated ID Type / Status
Subject Dingyuan County E302435 entity
Predicate notableResident P1092 FINISHED
Object Li Keqiang E54117 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: Li Keqiang | Statement: [Dingyuan County, notableResident, Li Keqiang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Li Keqiang
Context triple: [Dingyuan County, notableResident, Li Keqiang]
  • A. Li Keqiang chosen
    Li Keqiang was a Chinese economist and politician who served as the Premier of the People's Republic of China from 2013 to 2023.
  • B. Wen Jiabao
    Wen Jiabao is a Chinese politician who served as Premier of the People's Republic of China from 2003 to 2013.
  • C. Zhu Yunlai
    Zhu Yunlai is a Chinese banker and businessman, best known as the son of former Chinese premier Zhu Rongji and for his leadership roles in China’s financial sector.
  • D. Han Zheng
    Han Zheng is a Chinese politician and senior leader in the Communist Party of China who has held top roles in both national and Shanghai municipal governance.
  • E. Zhu Rongji
    Zhu Rongji is a prominent Chinese politician and reformist technocrat who served as Premier of the People's Republic of China from 1998 to 2003, overseeing major economic restructuring and market-oriented reforms.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9617c5b888190b37d4ede139bb49e completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ead66bc819099c8d274d69a2022 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:19 p.m.