Triple

T19232394
Position Surface form Disambiguated ID Type / Status
Subject E Embarcadero line E480902 entity
Predicate connectsTo P845 FINISHED
Object Muni 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: Muni bus network | Statement: [E Embarcadero line, connectsTo, Muni bus network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muni bus network
Context triple: [E Embarcadero line, connectsTo, Muni bus network]
  • A. Muni bus network chosen
    The Muni bus network is San Francisco’s citywide public transit system of buses and trolleybuses that provides comprehensive surface transportation across the city.
  • B. Muni Metro lines
    Muni Metro lines are a network of light rail routes in San Francisco that provide rapid transit service across the city as part of the San Francisco Municipal Railway system.
  • C. MUNI
    MUNI is the commonly used abbreviation for Masaryk University, a major public research university based in Brno, Czech Republic.
  • D. Muni Metro
    Muni Metro is San Francisco’s light rail and streetcar system, forming a core part of the city’s public transit network.
  • E. San Francisco trolleybus network
    The San Francisco trolleybus network is an electric public transit system of rubber-tired buses drawing power from overhead wires to serve routes throughout San Francisco.
  • 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa9db56081908f50d318d7fc9eaa completed April 20, 2026, 10:06 a.m.
Created at: April 10, 2026, 1:25 p.m.