Triple

T15639437
Position Surface form Disambiguated ID Type / Status
Subject Wuhan suburban districts E376028 entity
Predicate hasMember P10 FINISHED
Object Xinzhou District E599650 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: Xinzhou District | Statement: [Wuhan suburban districts, hasMember, Xinzhou District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xinzhou District
Context triple: [Wuhan suburban districts, hasMember, Xinzhou District]
  • A. Xinzhou District
    Xinzhou District is the central urban district and administrative hub of Shangrao City in Jiangxi Province, China.
  • B. Xinzhou District chosen
    Xinzhou District is an outlying district of Wuhan, China, known for its ongoing urban development and integration into the city’s metro network.
  • 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 District
    Datong District is an urban administrative district under the jurisdiction of Huainan City in Anhui Province, China, known for its role in the region’s coal industry and urban development.
  • E. Shangzhou District
    Shangzhou District is an urban administrative district in Shangluo, Shaanxi Province, China, serving as the city's political and economic 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed06b388190bfebb77fe70e7df1 completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f4b693c81908fd324a5e92fc23c completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:14 a.m.