Triple

T5701985
Position Surface form Disambiguated ID Type / Status
Subject Nightjet E125684 entity
Predicate hasRoute P4374 FINISHED
Object Vienna–Brussels
Vienna–Brussels is an international overnight rail connection linking Austria’s capital with Belgium’s capital, served by ÖBB’s Nightjet sleeper trains.
 E542981 NE FINISHED

How this triple was built (4 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: Vienna–Brussels | Statement: [Nightjet, hasRoute, Vienna–Brussels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vienna–Brussels
Context triple: [Nightjet, hasRoute, Vienna–Brussels]
  • A. Vienna–Hamburg
    Vienna–Hamburg is an international overnight rail connection linking Austria’s capital with the major German port city of Hamburg.
  • B. Paris–Vienna
    Paris–Vienna is the classic international rail corridor linking the French and Austrian capitals, historically served by luxury trains such as the Orient Express.
  • C. Frankfurt–Brussels
    Frankfurt–Brussels is a major international high-speed rail route linking Germany and Belgium, commonly served by InterCityExpress (ICE) trains.
  • D. Paris–Brussels
    Paris–Brussels is a major international high-speed rail corridor linking the capitals of France and Belgium.
  • E. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Vienna–Brussels
Triple: [Nightjet, hasRoute, Vienna–Brussels]
Generated description
Vienna–Brussels is an international overnight rail connection linking Austria’s capital with Belgium’s capital, served by ÖBB’s Nightjet sleeper trains.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vienna–Brussels
Target entity description: Vienna–Brussels is an international overnight rail connection linking Austria’s capital with Belgium’s capital, served by ÖBB’s Nightjet sleeper trains.
  • A. Vienna–Hamburg
    Vienna–Hamburg is an international overnight rail connection linking Austria’s capital with the major German port city of Hamburg.
  • B. Paris–Vienna
    Paris–Vienna is the classic international rail corridor linking the French and Austrian capitals, historically served by luxury trains such as the Orient Express.
  • C. Frankfurt–Brussels
    Frankfurt–Brussels is a major international high-speed rail route linking Germany and Belgium, commonly served by InterCityExpress (ICE) trains.
  • D. Paris–Brussels
    Paris–Brussels is a major international high-speed rail corridor linking the capitals of France and Belgium.
  • E. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • F. None of above. chosen

Provenance (5 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_69c0082c96988190b3a6a201edce472a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0245581988190a819b8137533ed31 completed March 22, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07de28424819090ff1f4a4b6cc9c0 completed March 22, 2026, 11:40 p.m.
NEDg Description generation batch_69c08bce3e808190af4e2f0e8591b2de completed March 23, 2026, 12:39 a.m.
NED2 Entity disambiguation (via description) batch_69c08c6d1a788190acb7651a1f144d9d completed March 23, 2026, 12:42 a.m.
Created at: March 22, 2026, 3:45 p.m.