Triple

T19483364
Position Surface form Disambiguated ID Type / Status
Subject Sundbyberg station E487446 entity
Predicate partOfNetwork P840 FINISHED
Object SL bus network NE NERFINISHED

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: SL bus network | Statement: [Sundbyberg station, partOfNetwork, SL bus network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SL bus network
Context triple: [Sundbyberg station, partOfNetwork, SL bus network]
  • A. STAR bus network
    The STAR bus network is the primary public bus system serving Rennes and its metropolitan area in France.
  • B. SL buses chosen
    SL buses are the public bus services operating within the Stockholm County public transport network in Sweden.
  • C. STM bus network
    The STM bus network is the extensive system of urban bus routes serving neighborhoods across the island of Montreal as part of the city’s public transit infrastructure.
  • D. Tan bus network
    The Tan bus network is the public transportation system serving the Nantes metropolitan area in western France, operating numerous bus routes that connect surrounding communes such as Saint-Sébastien-sur-Loire.
  • E. SMART bus network
    The SMART bus network is a regional public transit system serving the Detroit metropolitan area with fixed-route and paratransit bus services across multiple suburban communities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8e8d924388190b847cb15bb3d0aff completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6343c23308190a35f462f95338651 completed April 20, 2026, 2:12 p.m.
Created at: April 10, 2026, 1:39 p.m.