Triple

T18046433
Position Surface form Disambiguated ID Type / Status
Subject Bombardier REGIO E431786 entity
Predicate branding P1500 FINISHED
Object REGIO 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: REGIO | Statement: [Bombardier REGIO, branding, REGIO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: REGIO
Context triple: [Bombardier REGIO, branding, REGIO]
  • A. Regio chosen
    Regio is a regional train service brand in Switzerland operated by the Swiss Federal Railways (SBB/CFF/FFS), providing local and stopping services between towns and cities.
  • B. Regio 2N
    Regio 2N is a double-deck electric multiple unit train built by Bombardier (now Alstom) for regional and suburban services in France.
  • C. Rhegion
    Rhegion was an important ancient Greek city located at the southern tip of Italy, strategically positioned on the Strait of Messina.
  • D. regio of Italy
    A regio of Italy was a large territorial and administrative district used in ancient Roman regional organization of the Italian peninsula.
  • E. Regio IX
    Regio IX was one of the administrative regions of ancient Rome, encompassing the important public and religious area known as the Campus Martius.
  • 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_69d8b906482481908183315b9ecf9994 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4bff2d3c48190875ffe9c042d3ec0 completed April 19, 2026, 11:43 a.m.
Created at: April 10, 2026, 10:25 a.m.