Triple

T847063
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen E18299 entity
Predicate hasDistrict P459 FINISHED
Object Bao’an District E110200 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: Bao’an District | Statement: [Shenzhen, hasDistrict, Bao’an District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bao’an District
Context triple: [Shenzhen, hasDistrict, Bao’an District]
  • A. Fengtai District
    Fengtai District is an urban district in southwestern Beijing, China, known for its mix of residential, industrial, and historical areas, including the site of the Marco Polo Bridge.
  • B. Luohu District
    Luohu District is a central urban district of Shenzhen, China, known as one of the city’s oldest commercial hubs and a major gateway to Hong Kong.
  • C. Nanshan District
    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.
  • D. Bao’an chosen
    Bao’an is a historical county-level area in Guangdong, China, that once encompassed what is now the modern city of Shenzhen.
  • E. Xicheng District
    Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
  • 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_69a4938b04208190b82e1df6b572c548 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac0ba6b4819089c15ed7e1765502 completed March 1, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac16f749dc819097231c0becb4150b completed March 7, 2026, 12:15 p.m.
Created at: March 1, 2026, 7:38 p.m.