Triple

T13665994
Position Surface form Disambiguated ID Type / Status
Subject Yungang Grottoes E327121 entity
Predicate near P350 FINISHED
Object Datong city 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 city | Statement: [Yungang Grottoes, near, Datong city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Datong city
Context triple: [Yungang Grottoes, near, Datong city]
  • 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. 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.
  • D. Taiyuan
    Taiyuan was a historical Chinese era name used during the reign of the Eastern Jin emperor Sun Liang.
  • E. Baoding
    Baoding is a historic prefecture-level city in central Hebei Province, China, known as a regional transportation hub and former military and administrative center.
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc623fcc88190bbad97541c040b7a completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc315ff848190a6c8cbd5b90db7fc completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 9:52 p.m.