Triple

T21389155
Position Surface form Disambiguated ID Type / Status
Subject Xiangcheng District E527591 entity
Predicate borders P224 FINISHED
Object Gusu 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: Gusu District | Statement: [Xiangcheng District, borders, Gusu District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gusu District
Context triple: [Xiangcheng District, borders, Gusu District]
  • A. Gusu District chosen
    Gusu District is the central urban district of Suzhou, China, known for its historic canals, classical gardens, and well-preserved ancient cityscape.
  • B. Govuro District
    Govuro District is an administrative district located in Inhambane Province in southern Mozambique.
  • C. Rorya District
    Rorya District is an administrative district in northern Tanzania, located within the Mara Region near the shores of Lake Victoria.
  • D. Shinkay District
    Shinkay District is an administrative district located in Zabul Province in southern Afghanistan.
  • E. Hakui District
    Hakui District is a rural administrative district located in Ishikawa Prefecture on Japan’s Honshu island, known for its coastal landscapes and small towns.
  • 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_69e0b51ff3748190935c0a513c62a12b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee62cbfef08190a33ac1f198c82cd0 completed April 26, 2026, 7:09 p.m.
Created at: April 16, 2026, 5:12 p.m.