Triple

T18311844
Position Surface form Disambiguated ID Type / Status
Subject Wuzhou E438644 entity
Predicate borders P224 FINISHED
Object Guigang NE NERFINISHED

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: Guigang | Statement: [Wuzhou, borders, Guigang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guigang
Context triple: [Wuzhou, borders, Guigang]
  • A. Guigang chosen
    Guigang is a prefecture-level city in southeastern Guangxi, China, known as a regional transport hub and commercial center along the Xun River.
  • B. Wuzhou
    Wuzhou is a prefecture-level city in eastern Guangxi, China, known as a regional transport hub and commercial center along the Xi River.
  • C. 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.
  • D. Chongzuo
    Chongzuo is a prefecture-level city in southern China’s Guangxi region, known for its karst landscapes and location near the border with Vietnam.
  • E. Nanning
    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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50219cd548190b8da5f402d5da773 completed April 19, 2026, 4:26 p.m.
Created at: April 10, 2026, 10:36 a.m.