Triple

T18181965
Position Surface form Disambiguated ID Type / Status
Subject Qinzhou E435308 entity
Predicate hasSubdivision P747 FINISHED
Object Qinnan 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: Qinnan District | Statement: [Qinzhou, hasSubdivision, Qinnan District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Qinnan District
Context triple: [Qinzhou, hasSubdivision, Qinnan District]
  • A. Qinnan District chosen
    Qinnan District is an urban district that serves as the central administrative and commercial hub of Qinzhou in Guangxi, China.
  • B. Wuling District
    Wuling District is the central urban district and administrative hub of Changde City in Hunan Province, China.
  • C. Angangxi District
    Angangxi District is an urban district of Qiqihar in Heilongjiang Province, northeastern China, known historically for its industrial development and railway-related industries.
  • D. Weicheng District
    Weicheng District is an urban administrative district forming part of the city of Weifang in Shandong Province, China.
  • E. Tunxi District
    Tunxi District is the central urban district and main commercial hub of Huangshan City in Anhui Province, China, known as a gateway to the nearby Huangshan (Yellow Mountain) scenic area.
  • 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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dffb3bc88190a627be9c444d5c7d completed April 19, 2026, 2 p.m.
Created at: April 10, 2026, 10:31 a.m.