Triple

T1781327
Position Surface form Disambiguated ID Type / Status
Subject Eurostar E39296 entity
Predicate offersService P178 FINISHED
Object London–Paris
London–Paris is a major international rail route connecting the capitals of the United Kingdom and France via the Channel Tunnel.
 E199941 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: London–Paris | Statement: [Eurostar, offersService, London–Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: London–Paris
Context triple: [Eurostar, offersService, London–Paris]
  • A. New York–Paris
    New York–Paris is a major transatlantic air route connecting the United States and France, linking New York City with the French capital.
  • B. London–Edinburgh
    London–Edinburgh is a major intercity rail corridor in the United Kingdom linking the capital of England with the capital of Scotland.
  • C. Paris–Lille
    Paris–Lille is a major high-speed rail corridor in northern France connecting the capital Paris with the city of Lille.
  • D. Paris–Strasbourg
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • E. Calais
    Calais is a major French port city on the northern coast, serving as one of the primary crossing points between France and England.
  • 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: London–Paris
Triple: [Eurostar, offersService, London–Paris]
Generated description
London–Paris is a major international rail route connecting the capitals of the United Kingdom and France via the Channel Tunnel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: London–Paris
Target entity description: London–Paris is a major international rail route connecting the capitals of the United Kingdom and France via the Channel Tunnel.
  • A. New York–Paris
    New York–Paris is a major transatlantic air route connecting the United States and France, linking New York City with the French capital.
  • B. London–Edinburgh
    London–Edinburgh is a major intercity rail corridor in the United Kingdom linking the capital of England with the capital of Scotland.
  • C. Paris–Lille
    Paris–Lille is a major high-speed rail corridor in northern France connecting the capital Paris with the city of Lille.
  • D. Paris–Strasbourg
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • E. Calais
    Calais is a major French port city on the northern coast, serving as one of the primary crossing points between France and England.
  • 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64e22d6881909ba6ec120b320918 completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada99f52a08190854109d152c22be0 completed March 8, 2026, 4:53 p.m.
NEDg Description generation batch_69adab04b5688190afb3418e9b9da845 completed March 8, 2026, 4:59 p.m.
NED2 Entity disambiguation (via description) batch_69adaeaf81e881908f99f5d948e3557b completed March 8, 2026, 5:15 p.m.
Created at: March 4, 2026, 7:31 p.m.