Triple

T8276498
Position Surface form Disambiguated ID Type / Status
Subject Stuttgart Hauptbahnhof E193559 entity
Predicate serves P98 FINISHED
Object EuroCity E132580 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: EuroCity | Statement: [Stuttgart Hauptbahnhof, serves, EuroCity]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EuroCity
Context triple: [Stuttgart Hauptbahnhof, serves, EuroCity]
  • A. EuroCity trains chosen
    EuroCity trains are a network of high-quality international express passenger services that connect major cities across European countries with fast, comfortable, and cross-border rail travel.
  • B. InterCityExpress
    InterCityExpress is Germany’s high-speed train service operated by Deutsche Bahn, known for fast long-distance connections between major cities and neighboring countries.
  • C. Thalys
    Thalys is a high-speed international train service connecting major cities in France, Belgium, the Netherlands, and Germany.
  • D. 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.
  • E. Intercity Express Train
    The Intercity Express Train is a modern high-speed passenger train used on long-distance routes in the UK, known for faster journeys, improved comfort, and greater energy efficiency compared to older rolling stock.
  • 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_69ca82e14ae481908ffdb822cd2192bc completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb798d69508190b581ad8a38730175 completed March 31, 2026, 7:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd951c06b88190962b108b3325d30b completed April 1, 2026, 9:58 p.m.
Created at: March 30, 2026, 5:51 p.m.