Triple

T13032059
Position Surface form Disambiguated ID Type / Status
Subject The Last Emperor E326464 entity
Predicate setInLocation P40 FINISHED
Object Beijing E2312 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: Beijing | Statement: [The Last Emperor, setInLocation, Beijing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beijing
Context triple: [The Last Emperor, setInLocation, Beijing]
  • A. Beijing chosen
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • B. Tiāntán
    Tiāntán is the Chinese pinyin name for the Temple of Heaven, a historic imperial religious complex in Beijing where Ming and Qing dynasty emperors performed annual ceremonies to pray for good harvests.
  • C. Shanghai
    Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
  • D. Shanghai
    Shanghai is an unincorporated community located in Berkeley County, West Virginia, United States.
  • E. Shanghai
    Shanghai is a major Ethereum network upgrade that introduced key changes such as enabling staked ETH withdrawals and improving the protocol’s efficiency and flexibility.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97efe72348190b52fb4068f5fb829 completed April 10, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbb735e481909f120f95fa68f4f1 completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 8:54 p.m.