Triple

T4896660
Position Surface form Disambiguated ID Type / Status
Subject Orient Express E109698 entity
Predicate route P5619 FINISHED
Object Paris–Budapest
Paris–Budapest is a historic international rail connection linking the French and Hungarian capitals, notably served by the famed Orient Express.
 E477973 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–Budapest | Statement: [Orient Express, route, Paris–Budapest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paris–Budapest
Context triple: [Orient Express, route, Paris–Budapest]
  • A. Paris–Cologne
    Paris–Cologne is a major international high-speed rail route linking the French capital with the German city of Cologne.
  • B. Paris–Strasbourg
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • C. Paris–Toulouse
    Paris–Toulouse is a major intercity rail corridor in France linking the capital Paris with the southwestern city of Toulouse.
  • D. 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.
  • E. Paris–Bordeaux
    Paris–Bordeaux is a major high-speed rail corridor in France connecting the capital with the southwest, known for its fast TGV services.
  • 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–Budapest
Triple: [Orient Express, route, Paris–Budapest]
Generated description
Paris–Budapest is a historic international rail connection linking the French and Hungarian capitals, notably served by the famed Orient Express.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paris–Budapest
Target entity description: Paris–Budapest is a historic international rail connection linking the French and Hungarian capitals, notably served by the famed Orient Express.
  • A. Paris–Cologne
    Paris–Cologne is a major international high-speed rail route linking the French capital with the German city of Cologne.
  • B. Paris–Strasbourg
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • C. Paris–Toulouse
    Paris–Toulouse is a major intercity rail corridor in France linking the capital Paris with the southwestern city of Toulouse.
  • D. 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.
  • E. Paris–Bordeaux
    Paris–Bordeaux is a major high-speed rail corridor in France connecting the capital with the southwest, known for its fast TGV services.
  • 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.