Triple

T5099603
Position Surface form Disambiguated ID Type / Status
Subject RE E114950 entity
Predicate standsFor P590 FINISHED
Object RegioExpress E20911 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: RegioExpress | Statement: [RE, standsFor, RegioExpress]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RegioExpress
Context triple: [RE, standsFor, RegioExpress]
  • A. RegioExpress chosen
    RegioExpress is a category of Swiss regional express trains that provide relatively fast, limited-stop connections between major and medium-sized towns.
  • B. Regional-Express
    Regional-Express is a category of medium-distance passenger trains in Germany that provide relatively fast regional connections between cities and towns, operated under the Deutsche Bahn network.
  • C. InterRegio
    InterRegio is a category of medium- to long-distance passenger trains in several European countries that provides relatively fast regional connections between major cities and regions.
  • D. Leonardo Express train
    The Leonardo Express train is a dedicated non-stop rail service linking central Rome’s Termini station with Fiumicino Airport, providing a fast and frequent airport transfer for travelers.
  • E. TGV Lyria
    TGV Lyria is a high-speed train service linking France and Switzerland, operated as a joint venture between SNCF and Swiss Federal Railways.
  • 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_69bd443fc49c819089629c00e311310c completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7568e9c881909f114973faef6832 completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba8977f481908b0d55a9cd28d492 completed March 21, 2026, 3:34 p.m.
Created at: March 20, 2026, 1:40 p.m.