Triple

T5102392
Position Surface form Disambiguated ID Type / Status
Subject Giga Shanghai E115010 entity
Predicate locatedIn P40 FINISHED
Object Lingang E176778 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: Lingang | Statement: [Giga Shanghai, locatedIn, Lingang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lingang
Context triple: [Giga Shanghai, locatedIn, Lingang]
  • A. Lingang chosen
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • B. Jintao
    Jintao is the given name of Hu Jintao, the former President of the People's Republic of China and General Secretary of the Chinese Communist Party.
  • C. Zhaoyuan
    Zhaoyuan is a county-level city in eastern China's Shandong province, known for its rich gold mining industry and economic development.
  • D. 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.
  • E. Langfang
    Langfang is a prefecture-level city in northern China situated between Beijing and Tianjin, known for its strategic location and growing industrial and service sectors.
  • 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_69bd4440b3348190be1251fd8b7951f1 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7586a4a08190866aea6be625837c completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf330bc5c48190ad8ca1e413b6c68b completed March 22, 2026, 12:08 a.m.
Created at: March 20, 2026, 1:41 p.m.