Triple

T15175603
Position Surface form Disambiguated ID Type / Status
Subject Wanbailin District E362600 entity
Predicate subdivisionName1 P12497 FINISHED
Object Taiyuan E80116 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: Taiyuan | Statement: [Wanbailin District, subdivisionName1, Taiyuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taiyuan
Context triple: [Wanbailin District, subdivisionName1, Taiyuan]
  • A. Taiyuan chosen
    Taiyuan is the capital and largest city of Shanxi Province in northern China, known as an important industrial and transportation hub with a long imperial history.
  • B. Taiyuan
    Taiyuan was a historical Chinese era name used during the reign of the Eastern Jin emperor Sun Liang.
  • C. Xinzhou
    Xinzhou is a prefecture-level city in northern China known for its historical sites and location within Shanxi Province’s coal-rich and culturally significant region.
  • D. Datong
    Datong is a historic industrial city in northern China known for its coal production and nearby cultural landmarks such as the Yungang Grottoes.
  • E. Jinzhong
    Jinzhong is a prefecture-level city in northern China known for its historical sites and cultural heritage within Shanxi Province.
  • 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_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0066236d481909e8ac47f496861ad completed April 15, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fef88dd1fc8190b6cdabf6c24c2712 completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:09 a.m.