Triple

T16570823
Position Surface form Disambiguated ID Type / Status
Subject TGV Lyria E402577 entity
Predicate primaryRoute P6298 FINISHED
Object Paris–Basel
Paris–Basel is a major international rail corridor linking the French capital with the Swiss city of Basel.
 E442497 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–Basel | Statement: [TGV Lyria, primaryRoute, Paris–Basel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paris–Basel
Context triple: [TGV Lyria, primaryRoute, Paris–Basel]
  • A. Paris–Basel
    Paris–Basel is an international air route linking the French capital Paris with the Swiss city of Basel.
  • B. Paris–Lausanne
    Paris–Lausanne is an international high-speed rail route linking the French capital Paris with the Swiss city of Lausanne.
  • C. Paris–Geneva
    Paris–Geneva is a major international high-speed rail route linking the French capital with the Swiss city of Geneva.
  • D. Paris–Zurich
    Paris–Zurich is a major international high-speed rail corridor linking the French capital with Switzerland’s largest city.
  • E. Paris–Luxembourg
    Paris–Luxembourg is a major international railway route linking the French capital Paris with the Grand Duchy of Luxembourg.
  • 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–Basel
Triple: [TGV Lyria, primaryRoute, Paris–Basel]
Generated description
Paris–Basel is a major international rail corridor linking the French capital with the Swiss city of Basel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paris–Basel
Target entity description: Paris–Basel is a major international rail corridor linking the French capital with the Swiss city of Basel.
  • A. Paris–Basel chosen
    Paris–Basel is an international air route linking the French capital Paris with the Swiss city of Basel.
  • B. Paris–Lausanne
    Paris–Lausanne is an international high-speed rail route linking the French capital Paris with the Swiss city of Lausanne.
  • C. Paris–Geneva
    Paris–Geneva is a major international high-speed rail route linking the French capital with the Swiss city of Geneva.
  • D. Paris–Zurich
    Paris–Zurich is a major international high-speed rail corridor linking the French capital with Switzerland’s largest city.
  • E. Paris–Luxembourg
    Paris–Luxembourg is a major international railway route linking the French capital Paris with the Grand Duchy of Luxembourg.
  • F. None of above.

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_6a0084b077f481909796b5b60f501239 completed May 10, 2026, 1:14 p.m.
NEDg Description generation batch_6a008558218c8190b0e72356ae52afd2 completed May 10, 2026, 1:17 p.m.
NED2 Entity disambiguation (via description) batch_6a008624706881909e9a265a37eeb3fc completed May 10, 2026, 1:20 p.m.
Created at: April 10, 2026, 5:16 a.m.