Triple

T10865109
Position Surface form Disambiguated ID Type / Status
Subject Goslar station E256506 entity
Predicate servedByTrainOperator P20222 FINISHED
Object DB Regio Nord E825241 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: DB Regio Nord | Statement: [Goslar station, servedByTrainOperator, DB Regio Nord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DB Regio Nord
Context triple: [Goslar station, servedByTrainOperator, DB Regio Nord]
  • A. DB Regio
    DB Regio is a division of Germany’s national railway company that operates most of the country’s regional and local passenger train services.
  • B. 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.
  • C. RegioExpress
    RegioExpress is a category of Swiss regional express trains that provide relatively fast, limited-stop connections between major and medium-sized towns.
  • D. DB Regio Mitte chosen
    DB Regio Mitte is a regional division of Deutsche Bahn responsible for operating local and regional passenger train services in central Germany.
  • E. Arvato
    Arvato is a global business process outsourcing and services provider specializing in customer relationship management, supply chain management, and digital solutions.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7516b2f148190adbacd35fc8c2056 completed April 9, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7d5359c8190b46a6b817938eb67 completed April 15, 2026, 8:40 p.m.
Created at: April 8, 2026, 9:20 p.m.