Triple

T13443052
Position Surface form Disambiguated ID Type / Status
Subject Zhejiang Geely Holding Group E320412 entity
Predicate keyPerson P256 FINISHED
Object Li Shufu E1041728 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 Shufu | Statement: [Zhejiang Geely Holding Group, keyPerson, Li Shufu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Li Shufu
Context triple: [Zhejiang Geely Holding Group, keyPerson, Li Shufu]
  • A. Li Shufu chosen
    Li Shufu is a Chinese billionaire entrepreneur best known as the founder and chairman of Geely, one of China’s largest private automakers and a major global automotive investor.
  • B. Zeng Liansong
    Zeng Liansong was a Chinese designer best known for creating the national flag of the People's Republic of China.
  • C. Xu Guangda
    Xu Guangda was a prominent Chinese military commander and founding general of the People's Liberation Army who played key roles in the Chinese Civil War and early PRC military development.
  • D. Yuan Jiahua
    Yuan Jiahua was a prominent Chinese linguist known for his influential work on Chinese dialectology and the classification of Chinese languages.
  • E. Liu Xianshi
    Liu Xianshi was a Chinese military and political figure from Yunnan who rose to prominence as a warlord during the early Republican era.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee881888190811ddf01bc699864 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d8892a88190b4a32865b32c8883 completed May 3, 2026, 2:36 p.m.
Created at: April 9, 2026, 9:40 p.m.