Triple

T22716001
Position Surface form Disambiguated ID Type / Status
Subject Huishan Ancient Town E561733 entity
Predicate partOf P40 FINISHED
Object Liangxi District NE NERFINISHED

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: Liangxi District | Statement: [Huishan Ancient Town, partOf, Liangxi District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liangxi District
Context triple: [Huishan Ancient Town, partOf, Liangxi District]
  • A. Liangxi District chosen
    Liangxi District is a central urban district of Wuxi in Jiangsu Province, China, known as one of the city’s key commercial and administrative areas.
  • B. Fengnan District
    Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
  • C. Linxiang District
    Linxiang District is an urban administrative district that serves as the central seat of Lincang City in Yunnan Province, China.
  • D. Qintang District
    Qintang District is an urban administrative district within the prefecture-level city of Guigang in Guangxi, southern China.
  • E. Yuyang District
    Yuyang District is an urban administrative district and the central area of Yulin City in northern Shaanxi Province, China.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2454fc984819088213b58ee87a002 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1790ca59881909064d49f331fb711 completed April 29, 2026, 3:20 a.m.
Created at: April 17, 2026, 3:19 p.m.