Triple

T8407347
Position Surface form Disambiguated ID Type / Status
Subject Zhou Yu E198531 entity
Predicate associatedWith P37 FINISHED
Object Jiangdong E661706 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: Jiangdong | Statement: [Zhou Yu, associatedWith, Jiangdong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jiangdong
Context triple: [Zhou Yu, associatedWith, Jiangdong]
  • A. Jiangdong chosen
    Jiangdong is a historical region in southeastern China along the lower Yangtze River, known as the core territory and power base of the Eastern Wu state during the Three Kingdoms period.
  • B. Qianjiang
    Qianjiang is a city in China known for its regional industry and cultural exchanges, including international town twinning partnerships.
  • C. Yuezhou
    Yuezhou is the historical name of the city now known as Yueyang, an important cultural and transport hub in Hunan Province, China.
  • D. Huangchu
    Huangchu was the first era name of the Cao Wei state during China’s Three Kingdoms period, marking the early reign of Emperor Cao Pi.
  • E. Dongqing
    Dongqing is a coastal village on Orchid Island in Taiwan, known for its indigenous Tao culture and scenic Pacific shoreline.
  • 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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb831409308190981089c303ebaef4 completed March 31, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce03035e148190867b60ddaeb8d761 completed April 2, 2026, 5:47 a.m.
Created at: March 30, 2026, 6:05 p.m.