Triple

T7728231
Position Surface form Disambiguated ID Type / Status
Subject Ma Yansong E175184 entity
Predicate hasWorkLocation P1527 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: [Ma Yansong, hasWorkLocation, Beijing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beijing
Context triple: [Ma Yansong, hasWorkLocation, 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 a major Ethereum network upgrade that introduced key changes such as enabling staked ETH withdrawals and improving the protocol’s efficiency and flexibility.
  • E. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70315e8e88190a5c7e5d2f2ef66bc completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8d69516a88190912a9574aef3d1f8 completed March 29, 2026, 7:36 a.m.
Created at: March 27, 2026, 4:06 p.m.