Triple

T15682669
Position Surface form Disambiguated ID Type / Status
Subject Beijing MTR E377615 entity
Predicate networkIntegrationWith P42454 FINISHED
Object Beijing Subway E12220 NE FINISHED

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: Beijing Subway | Statement: [Beijing MTR, networkIntegrationWith, Beijing Subway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Beijing Subway
Context triple: [Beijing MTR, networkIntegrationWith, Beijing Subway]
  • A. Beijing Subway chosen
    The Beijing Subway is one of the world’s largest and busiest rapid transit systems, forming the backbone of public transportation in China’s capital city.
  • B. Beijing MTR
    Beijing MTR is a railway and metro operating company responsible for running several lines of the Beijing Subway in partnership with the city government.
  • C. Shanghai Metro
    Shanghai Metro is one of the world’s largest and busiest rapid transit systems, serving the city of Shanghai with an extensive network of urban and suburban rail lines.
  • D. Beijing Suburban Railway
    Beijing Suburban Railway is a commuter rail network serving the greater Beijing metropolitan area, connecting urban districts with surrounding suburban regions.
  • E. Tianjin Metro
    Tianjin Metro is the rapid transit system serving the city of Tianjin, China, providing urban and suburban rail transportation across the municipality.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: networkIntegrationWith
Context triple: [Beijing MTR, networkIntegrationWith, Beijing Subway]
  • A. hasSocialNetworkingIntegration
    Indicates that an entity is connected to or supports interaction with one or more social networking platforms.
  • B. integrationProperty
    Indicates a relationship where one entity serves as a property, parameter, or configuration aspect governing how another entity is integrated or combined with systems, components, or processes.
  • C. integrationFeature
    Indicates that one entity provides a capability or component specifically intended to enable or support integration with another system, service, or component.
  • D. typeOfIntegration
    Indicates the specific kind or category of integration that exists or is applied between systems, components, or processes.
  • E. linkedNetwork chosen
    Indicates that two entities are connected through a shared or associated network relationship.
  • F. None of above.

Provenance (4 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f31b5b881908e46ecd9fc6048ab completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ee4c8688190ae2fefb56171161a completed May 9, 2026, 5:29 p.m.
PD Predicate disambiguation batch_69deda8c856c8190882330114f9a1a5f completed April 15, 2026, 12:23 a.m.
Created at: April 10, 2026, 4:16 a.m.