Triple

T7183382
Position Surface form Disambiguated ID Type / Status
Subject Chizhou E167508 entity
Predicate hasSubdivision P747 FINISHED
Object Guichi District E647773 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: Guichi District | Statement: [Chizhou, hasSubdivision, Guichi District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guichi District
Context triple: [Chizhou, hasSubdivision, Guichi District]
  • A. Guichi District chosen
    Guichi District is an urban district that serves as the central administrative and commercial hub of Chizhou in Anhui Province, China.
  • B. Nishiusuki District
    Nishiusuki District is a rural administrative district in Miyazaki Prefecture, Japan, known for its mountainous terrain and small towns such as Takachiho.
  • C. Ominato District
    Ominato District is a regional command of the Japan Maritime Self-Defense Force responsible for naval operations and defense in the northern waters of Japan.
  • D. Miura District
    Miura District is a rural administrative district in Kanagawa Prefecture, Japan, known for its coastal towns and scenic Miura Peninsula landscapes.
  • E. Soraku District
    Soraku District is a rural administrative district located in the southern part of Kyoto Prefecture, Japan, known for its small towns and agricultural landscapes.
  • 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_69c6888a7c548190a3d39b52a393080f completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e8bd52648190a22412300254e5d4 completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bf8d76ac8190a2e29f2650e7af28 completed March 28, 2026, 11:46 a.m.
Created at: March 27, 2026, 2:49 p.m.