Triple

T14570441
Position Surface form Disambiguated ID Type / Status
Subject 国务院秘书长 E341896 entity
Predicate officeLocation P40 FINISHED
Object 北京市 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: 北京市 | Statement: [国务院秘书长, officeLocation, 北京市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 北京市
Context triple: [国务院秘书长, officeLocation, 北京市]
  • 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. Tân An
    Tân An is a city in southern Vietnam that serves as an administrative, economic, and cultural hub in the Mekong Delta region.
  • C. Haidian District
    Haidian District is a major urban district in northwest Beijing known for its universities, technology hubs, and historic imperial gardens.
  • D. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • E. 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.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f2121481908f2385637944785d completed April 14, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ac858108190b7c90130f18b0ddb completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:23 a.m.