Triple

T3061677
Position Surface form Disambiguated ID Type / Status
Subject Yan Mountains E62009 entity
Predicate locatedIn P40 FINISHED
Object Tianjin Municipality E31338 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: Tianjin Municipality | Statement: [Yan Mountains, locatedIn, Tianjin Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tianjin Municipality
Context triple: [Yan Mountains, locatedIn, Tianjin Municipality]
  • A. Tianjin chosen
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • 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. Pinghu City
    Pinghu City is a county-level coastal city in northern Zhejiang Province, China, known for its manufacturing industry and proximity to Shanghai across Hangzhou Bay.
  • D. 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.
  • E. Beijing
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9e9f33d88190bd481cb7f18ceb91 completed March 8, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b261e211c0819094ef28112bcad250 completed March 12, 2026, 6:49 a.m.
Created at: March 8, 2026, 3:02 p.m.