Triple

T9823594
Position Surface form Disambiguated ID Type / Status
Subject Sanya E238596 entity
Predicate hasDistrict P459 FINISHED
Object Haitang District E875111 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: Haitang District | Statement: [Sanya, hasDistrict, Haitang District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haitang District
Context triple: [Sanya, hasDistrict, Haitang District]
  • A. Neihu District
    Neihu District is a suburban and technology-focused district in northeastern Taipei, Taiwan, known for its science parks, residential communities, and natural scenery.
  • B. Tianya District chosen
    Tianya District is an administrative district of the city of Sanya in Hainan Province, China, known for its coastal tourism and tropical scenery.
  • C. Fengnan District
    Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
  • D. Daiyue District
    Daiyue District is an administrative district under the jurisdiction of Tai'an City in Shandong Province, China, known for encompassing part of the Mount Tai scenic area.
  • E. Jiawang District
    Jiawang District is an administrative district under the jurisdiction of Xuzhou in Jiangsu Province, eastern China, known historically for its coal mining industry.
  • 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb316f8948190ada3738787a5cb6a completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d979c21f5481908bea7fd2c70d2c0b completed April 10, 2026, 10:29 p.m.
Created at: March 30, 2026, 8:31 p.m.