Triple

T16570822
Position Surface form Disambiguated ID Type / Status
Subject TGV Lyria E402577 entity
Predicate primaryRoute P6298 FINISHED
Object Paris–Zurich
Paris–Zurich is a major international high-speed rail corridor linking the French capital with Switzerland’s largest city.
 E1225071 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–Zurich | Statement: [TGV Lyria, primaryRoute, Paris–Zurich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paris–Zurich
Context triple: [TGV Lyria, primaryRoute, Paris–Zurich]
  • A. Paris–Lausanne
    Paris–Lausanne is an international high-speed rail route linking the French capital Paris with the Swiss city of Lausanne.
  • B. Paris–Geneva
    Paris–Geneva is a major international high-speed rail route linking the French capital with the Swiss city of Geneva.
  • C. Paris–Basel
    Paris–Basel is an international air route linking the French capital Paris with the Swiss city of Basel.
  • D. Zurich
    Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
  • E. Stettlen
    Stettlen is a municipality in the canton of Bern in Switzerland, situated just east of the city of Bern and functioning largely as a residential and commuter community.
  • 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–Zurich
Triple: [TGV Lyria, primaryRoute, Paris–Zurich]
Generated description
Paris–Zurich is a major international high-speed rail corridor linking the French capital with Switzerland’s largest city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paris–Zurich
Target entity description: Paris–Zurich is a major international high-speed rail corridor linking the French capital with Switzerland’s largest city.
  • A. Paris–Lausanne
    Paris–Lausanne is an international high-speed rail route linking the French capital Paris with the Swiss city of Lausanne.
  • B. Paris–Geneva
    Paris–Geneva is a major international high-speed rail route linking the French capital with the Swiss city of Geneva.
  • C. Paris–Basel
    Paris–Basel is an international air route linking the French capital Paris with the Swiss city of Basel.
  • D. Zurich
    Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
  • E. Stettlen
    Stettlen is a municipality in the canton of Bern in Switzerland, situated just east of the city of Bern and functioning largely as a residential and commuter community.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35958d49c8190b995188240fb355b completed April 18, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a007da4b60c8190a682d20aa881792c completed May 10, 2026, 12:44 p.m.
NEDg Description generation batch_6a00805a84388190ac989129745e8234 completed May 10, 2026, 12:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0080abae0c81908c827dced1b56aa6 completed May 10, 2026, 12:57 p.m.
Created at: April 10, 2026, 5:16 a.m.