Triple

T4723269
Position Surface form Disambiguated ID Type / Status
Subject Nanshan Subdistrict E104819 entity
Predicate locatedIn P40 FINISHED
Object Nanshan District E111435 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: Nanshan District | Statement: [Nanshan Subdistrict, locatedIn, Nanshan District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanshan District
Context triple: [Nanshan Subdistrict, locatedIn, Nanshan District]
  • A. Nanshan District chosen
    Nanshan District is a major urban district of Shenzhen, China, known as a key technology and innovation hub that hosts many leading tech companies and research institutions.
  • B. Tianxin District
    Tianxin District is a central urban district of Changsha, the capital city of Hunan Province in China, known for its historical sites and commercial areas.
  • 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. Wanhua District
    Wanhua District is one of Taipei’s oldest urban areas, known for its historic temples, traditional markets, and the popular shopping and entertainment area of Ximending.
  • E. 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.
  • 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_69bd43ed84648190ae0b7ee8e8d00482 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6444412c81908a7f6f17978df2d2 completed March 20, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfdeaa224c8190a115d8af390eea71 completed March 22, 2026, 12:20 p.m.
Created at: March 20, 2026, 1:18 p.m.