Triple

T13803428
Position Surface form Disambiguated ID Type / Status
Subject Yungang Grottoes E331697 entity
Predicate locatedIn P40 FINISHED
Object Datong E331697 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: Datong | Statement: [Yungang Grottoes, locatedIn, Datong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Datong
Context triple: [Yungang Grottoes, locatedIn, Datong]
  • A. Datong chosen
    Datong is a historic industrial city in northern China known for its coal production and nearby cultural landmarks such as the Yungang Grottoes.
  • B. 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.
  • C. Fenyang
    Fenyang is a county-level city in Shanxi Province, China, known for its historical heritage and role in regional commerce and culture.
  • D. Taiyuan
    Taiyuan was a historical Chinese era name used during the reign of the Eastern Jin emperor Sun Liang.
  • E. Taiyuan
    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.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026c36108190a7436034a730a261 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd323be8d48190b0b289f25de06fb1 completed May 8, 2026, 12:45 a.m.
Created at: April 9, 2026, 10:12 p.m.