Triple

T12215215
Position Surface form Disambiguated ID Type / Status
Subject School of Economics, Nankai University E291064 entity
Predicate locatedIn P40 FINISHED
Object Tianjin 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 | Statement: [School of Economics, Nankai University, locatedIn, Tianjin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tianjin
Context triple: [School of Economics, Nankai University, locatedIn, Tianjin]
  • A. Tianjin chosen
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • 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. 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.
  • D. Beijing
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • E. Zhongdu
    Zhongdu was the historical capital city of the Jurchen-led Jin dynasty in northern China, located in what is now part of modern Beijing.
  • 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_69d6ab65923081909acfc61b7a612233 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c931cec819083ca19be06a33e1c completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63ee89b28819095e2e5df8acbcb22 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:51 p.m.