Triple

T4299562
Position Surface form Disambiguated ID Type / Status
Subject Guangxi Zhuang Autonomous Region E99799 entity
Predicate capital P234 FINISHED
Object Nanning E185263 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: Nanning | Statement: [Guangxi Zhuang Autonomous Region, capital, Nanning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanning
Context triple: [Guangxi Zhuang Autonomous Region, capital, Nanning]
  • A. Nanning chosen
    Nanning is the capital and largest city of China’s Guangxi Zhuang Autonomous Region, known as a key economic hub and “Green City” in the Lingnan cultural area.
  • B. Liuzhou
    Liuzhou is a major industrial city in the Guangxi Zhuang Autonomous Region of southern China, known for its heavy industry, transportation hub status, and distinctive karst landscape.
  • C. Anshun
    Anshun is a prefecture-level city in southwestern China known for its karst landscapes, including the famous Huangguoshu Waterfall, and its location within Guizhou Province.
  • D. Guilin
    Guilin is a scenic city in southern China’s Guangxi region, famed for its dramatic karst mountains and picturesque Li River landscapes.
  • E. Guiyang
    Guiyang is the capital city of Guizhou Province in southwest China, known for its cool climate, karst landscapes, and role as a regional transportation and industrial hub.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509e8cb481909ccca7992aac31a3 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c74a1a7c8190a69a82a8a2a38db9 completed March 14, 2026, 8:38 p.m.
Created at: March 12, 2026, 11:08 p.m.