Triple

T11428404
Position Surface form Disambiguated ID Type / Status
Subject FlixBus E270812 entity
Predicate formerName P65 FINISHED
Object MeinFernbus FlixBus E270812 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: MeinFernbus FlixBus | Statement: [FlixBus, formerName, MeinFernbus FlixBus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MeinFernbus FlixBus
Context triple: [FlixBus, formerName, MeinFernbus FlixBus]
  • A. FlixBus chosen
    FlixBus is a long-distance intercity bus company offering low-cost coach travel across numerous cities in North America and Europe.
  • B. DB Regio Bus
    DB Regio Bus is the regional and local bus transport division of Deutsche Bahn, operating extensive bus services across Germany.
  • C. TMB Bus Turístic app
    The TMB Bus Turístic app is a mobile application that helps users plan, navigate, and access information about Barcelona’s official tourist bus routes and services.
  • D. DB Fernverkehr
    DB Fernverkehr is the long-distance passenger rail division of Germany’s national railway company, operating Intercity, Eurocity, and high-speed ICE train services across Germany and neighboring countries.
  • E. Megabus
    Megabus is a low-cost intercity coach service known for operating long-distance bus routes across major cities in North America and Europe.
  • 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d806c000b88190bfaa646b2dc424b7 completed April 9, 2026, 8:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b8d923688190bb4d61d57768e10e completed April 20, 2026, 5:25 a.m.
Created at: April 8, 2026, 9:35 p.m.