Triple

T9547132
Position Surface form Disambiguated ID Type / Status
Subject Lincang E230320 entity
Predicate administrativeCenter P1474 FINISHED
Object Linxiang District E847842 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: Linxiang District | Statement: [Lincang, administrativeCenter, Linxiang District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linxiang District
Context triple: [Lincang, administrativeCenter, Linxiang District]
  • A. Linxiang District chosen
    Linxiang District is an urban administrative district that serves as the central seat of Lincang City in Yunnan Province, China.
  • B. Zhengxiang District
    Zhengxiang District is an urban administrative district of Hengyang City in Hunan Province, China, known for its role as one of the city's central built-up areas.
  • C. Fengnan District
    Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
  • D. Jiancaoping District
    Jiancaoping District is an urban district of Taiyuan, the capital city of Shanxi Province in northern China, known for its industrial development and residential areas.
  • E. Jiawang District
    Jiawang District is an administrative district under the jurisdiction of Xuzhou in Jiangsu Province, eastern China, known historically for its coal mining industry.
  • 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_69ca847c70b8819088a0a0bad64a50d6 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9904732c8190ab60ecc47c995cbe completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d354af200881909b08ab9b71d0d53f completed April 6, 2026, 6:37 a.m.
Created at: March 30, 2026, 8:02 p.m.