Triple

T19461362
Position Surface form Disambiguated ID Type / Status
Subject Beihuan Boulevard E486878 entity
Predicate partOf P40 FINISHED
Object Shenzhen road network NE NERFINISHED

How this triple was built (3 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: Shenzhen road network | Statement: [Beihuan Boulevard, partOf, Shenzhen road network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shenzhen road network
Context triple: [Beihuan Boulevard, partOf, Shenzhen road network]
  • A. Hong Kong road network
    The Hong Kong road network is a dense, highly developed system of highways, tunnels, bridges, and urban streets that supports the territory’s intensive traffic and connects its major districts and outlying areas.
  • B. Zhuhai urban transport network
    The Zhuhai urban transport network is the integrated system of local buses, rail links, and other public transit services that facilitates movement within Zhuhai and connects it to surrounding cities in the Pearl River Delta.
  • C. Beijing urban road network
    The Beijing urban road network is an extensive, hierarchical system of ring roads, arterial avenues, and expressways that organizes and connects the Chinese capital’s dense urban fabric and surrounding metropolitan area.
  • D. Taipei road network
    The Taipei road network is an extensive urban transportation system of highways, arterial roads, bridges, and streets that supports the dense traffic and connectivity needs of Taiwan’s capital city.
  • E. expressways of Shenzhen
    The expressways of Shenzhen form a dense, modern highway network that connects its urban districts and surrounding regions, supporting the city’s rapid economic growth and high-volume traffic.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Shenzhen road network
Target entity description: The Shenzhen road network is an extensive, high-capacity urban roadway system that connects and supports the fast-growing metropolis of Shenzhen, China.
  • A. Hong Kong road network
    The Hong Kong road network is a dense, highly developed system of highways, tunnels, bridges, and urban streets that supports the territory’s intensive traffic and connects its major districts and outlying areas.
  • B. Zhuhai urban transport network
    The Zhuhai urban transport network is the integrated system of local buses, rail links, and other public transit services that facilitates movement within Zhuhai and connects it to surrounding cities in the Pearl River Delta.
  • C. Beijing urban road network
    The Beijing urban road network is an extensive, hierarchical system of ring roads, arterial avenues, and expressways that organizes and connects the Chinese capital’s dense urban fabric and surrounding metropolitan area.
  • D. Taipei road network
    The Taipei road network is an extensive urban transportation system of highways, arterial roads, bridges, and streets that supports the dense traffic and connectivity needs of Taiwan’s capital city.
  • E. expressways of Shenzhen chosen
    The expressways of Shenzhen form a dense, modern highway network that connects its urban districts and surrounding regions, supporting the city’s rapid economic growth and high-volume traffic.
  • F. None of above.

Provenance (2 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633c983f481908b2684dc4380b889 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:38 p.m.