Triple

T18311845
Position Surface form Disambiguated ID Type / Status
Subject Wuzhou E438644 entity
Predicate borders P224 FINISHED
Object Yulin 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: Yulin | Statement: [Wuzhou, borders, Yulin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yulin
Context triple: [Wuzhou, borders, Yulin]
  • A. Yulin chosen
    Yulin is a prefecture-level city in northern China known for its coal resources and location on the Loess Plateau near the border with Inner Mongolia.
  • B. Yulin
    Yulin is a prefecture-level city in southeastern China known for its role as a regional commercial hub and for its controversial annual dog meat festival.
  • C. Tongchuan
    Tongchuan is a prefecture-level city in central Shaanxi Province, China, historically known for its coal mining industry and location on the Loess Plateau.
  • D. Huayin City
    Huayin City is a county-level city in Shaanxi Province, China, best known as the gateway to the famous Mount Hua, one of China’s Five Great Mountains.
  • E. Baoji
    Baoji is a major industrial and transportation hub city in western Shaanxi Province, China, known for its manufacturing base and historical sites.
  • 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.