Triple

T6023576
Position Surface form Disambiguated ID Type / Status
Subject Qiaokou District E134120 entity
Predicate borders P224 FINISHED
Object Jianghan District E70518 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: Jianghan District | Statement: [Qiaokou District, borders, Jianghan District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jianghan District
Context triple: [Qiaokou District, borders, Jianghan District]
  • A. Jianghan District chosen
    Jianghan District is a central urban district of Wuhan, Hubei Province, known for its commercial hubs and historical and cultural sites.
  • B. Wuchang District
    Wuchang District is a central urban district of Wuhan, China, known for its historical significance, educational institutions, and location along the Yangtze River.
  • C. Qianjiang District
    Qianjiang District is an administrative district in southeastern Chongqing, China, known for its mountainous terrain and role as a regional transport and economic hub.
  • D. Furong District
    Furong District is a central urban district of Changsha, the capital city of Hunan Province in China, known for its commercial activity and administrative importance.
  • E. Huangshigang District
    Huangshigang District is an urban administrative district and central area of the prefecture-level city of Huangshi in Hubei Province, China.
  • 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_69c008742a5c8190b9cb9c2787a3d8b3 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04fbd7978819085d683578bc62aa3 completed March 22, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11371ceb88190b0c2d4218ed0327a completed March 23, 2026, 10:18 a.m.
Created at: March 22, 2026, 4:07 p.m.