Triple

T5035289
Position Surface form Disambiguated ID Type / Status
Subject Luohu District E113404 entity
Predicate adjacentTo P224 FINISHED
Object Pingshan District E120896 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: Pingshan District | Statement: [Luohu District, adjacentTo, Pingshan District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pingshan District
Context triple: [Luohu District, adjacentTo, Pingshan District]
  • A. Pingshan District chosen
    Pingshan District is an administrative district in the eastern part of Shenzhen, China, known for its emerging high-tech industries and rapid urban development.
  • B. Xinbei District
    Xinbei District is a major urban district and economic hub of Changzhou in Jiangsu Province, China, known for its modern development and industrial zones.
  • C. Haizhu District
    Haizhu District is a central urban district of Guangzhou, China, known for its mix of residential areas, commercial centers, and cultural sites along the Pearl River.
  • D. Xiangzhou District
    Xiangzhou District is the central urban district of Zhuhai in Guangdong Province, China, known for its government, commercial, and coastal areas facing Macau.
  • E. Guangming District
    Guangming District is a rapidly developing suburban district in northwestern Shenzhen, China, known for its emerging high-tech industries and residential communities.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73b9ad488190a2a8c4da8858eb91 completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1132b29ac819086654ae935e819ef completed March 23, 2026, 10:17 a.m.
Created at: March 20, 2026, 1:36 p.m.