Triple

T12147290
Position Surface form Disambiguated ID Type / Status
Subject Changzhou Metro E289357 entity
Predicate serves P98 FINISHED
Object Xinbei District E334471 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: Xinbei District | Statement: [Changzhou Metro, serves, Xinbei District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xinbei District
Context triple: [Changzhou Metro, serves, Xinbei District]
  • A. Xinbei District chosen
    Xinbei District is a major urban district and economic hub of Changzhou in Jiangsu Province, China, known for its modern development and industrial zones.
  • B. Sanshui District
    Sanshui District is an administrative district of Foshan City in Guangdong Province, China, known for its manufacturing base and location within the Pearl River Delta economic region.
  • C. Shuangxi District
    Shuangxi District is a rural, mountainous district in eastern New Taipei City, Taiwan, known for its rivers, old streets, and natural scenery.
  • D. Baoan District
    Baoan District is a major administrative district in Shenzhen, China, known as one of the city’s original and rapidly developing industrial and residential hubs.
  • E. 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.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915ac2ebc81909155f9b2fb4a2252 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65e9868ec81909efd7e142d5fb090 completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 9:49 p.m.