Triple

T15275250
Position Surface form Disambiguated ID Type / Status
Subject Jinyuan District E365120 entity
Predicate isUrbanAreaOf P12103 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: [Jinyuan District, isUrbanAreaOf, Taiyuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taiyuan
Context triple: [Jinyuan District, isUrbanAreaOf, 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00952731c8190bf6a5e6e10c95b94 completed April 15, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff21945b60819098ea91d9693cb8e3 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:14 a.m.