Triple

T4896659
Position Surface form Disambiguated ID Type / Status
Subject Orient Express E109698 entity
Predicate route P5619 FINISHED
Object 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.
 E477972 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: Paris–Vienna | Statement: [Orient Express, route, Paris–Vienna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paris–Vienna
Context triple: [Orient Express, route, Paris–Vienna]
  • A. Paris–Prague
    Paris–Prague was an international air route connecting the French and Czech capitals, served by the early 20th-century French airline Air Union.
  • B. Vienne
    Vienne is a historic town in southeastern France known for its well-preserved Roman and medieval heritage, including ancient temples, a Roman theater, and a Gothic cathedral.
  • C. Vienne
    Vienne is a major river in west-central France that flows through the Limousin region before joining the Loire.
  • D. Paris–Brussels
    Paris–Brussels is a major international high-speed rail corridor linking the capitals of France and Belgium.
  • E. Moscow–Paris
    Moscow–Paris is a major international air route linking the capitals of Russia and France.
  • 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: Paris–Vienna
Triple: [Orient Express, route, Paris–Vienna]
Generated description
Paris–Vienna is the classic international rail corridor linking the French and Austrian capitals, historically served by luxury trains such as the Orient Express.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paris–Vienna
Target entity description: Paris–Vienna is the classic international rail corridor linking the French and Austrian capitals, historically served by luxury trains such as the Orient Express.
  • A. Paris–Prague
    Paris–Prague was an international air route connecting the French and Czech capitals, served by the early 20th-century French airline Air Union.
  • B. Vienne
    Vienne is a historic town in southeastern France known for its well-preserved Roman and medieval heritage, including ancient temples, a Roman theater, and a Gothic cathedral.
  • C. Vienne
    Vienne is a major river in west-central France that flows through the Limousin region before joining the Loire.
  • D. Paris–Brussels
    Paris–Brussels is a major international high-speed rail corridor linking the capitals of France and Belgium.
  • E. Moscow–Paris
    Moscow–Paris is a major international air route linking the capitals of Russia and France.
  • 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_69bd4410bbf88190aad50d2451c863d6 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e2923a081909bd592880b6f399b completed March 20, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fc997548190bb340193475065ee completed March 21, 2026, 10:15 a.m.
NEDg Description generation batch_69be70585e9881909b8ad633f6cc42a6 completed March 21, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_69be70d49768819088f4d523e968fdfb completed March 21, 2026, 10:20 a.m.
Created at: March 20, 2026, 1:28 p.m.