Triple

T9944239
Position Surface form Disambiguated ID Type / Status
Subject Sun Xiu E194161 entity
Predicate region P40 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: [Sun Xiu, region, Jiangdong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jiangdong
Context triple: [Sun Xiu, region, 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. Jingnan
    Jingnan was a small regional kingdom in south-central China that existed during the Five Dynasties and Ten Kingdoms period.
  • E. 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.
  • 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_69ca82e409348190a393777356b80a2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb613fbb48190b82a06987310cc96 completed April 2, 2026, 12:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2291a22f88190acf055a7410c1808 completed April 5, 2026, 9:19 a.m.
Created at: March 30, 2026, 8:45 p.m.