Triple

T15299387
Position Surface form Disambiguated ID Type / Status
Subject M2 (Lausanne Metro) E365743 entity
Predicate servesStation P839 FINISHED
Object Vennes
Vennes is a metro station on Lausanne’s M2 line in Switzerland, serving the eastern part of the city near the Olympic Museum and local residential areas.
 E1149172 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: Vennes | Statement: [M2 (Lausanne Metro), servesStation, Vennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vennes
Context triple: [M2 (Lausanne Metro), servesStation, Vennes]
  • A. Verran
    Verran is a former municipality in Trøndelag county, Norway, known for its rural landscapes, forestry, and fjord-side settlements.
  • B. Vennachar
    Vennachar is a small rural community located within the township of Addington Highlands in eastern Ontario, Canada.
  • C. Villeneuviens
    Villeneuviens are the inhabitants of the French commune of Villeneuve-sur-Yonne in the Yonne department of Bourgogne-Franche-Comté.
  • D. Veniste
    Veniste is a component or subdivision associated with Ben-Veniste, likely representing a related name, branch, or derivative entity.
  • E. Vestnes
    Vestnes is a municipality and village in western Norway known for its coastal location along the Romsdalsfjord and its role as a local administrative and service center.
  • 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: Vennes
Triple: [M2 (Lausanne Metro), servesStation, Vennes]
Generated description
Vennes is a metro station on Lausanne’s M2 line in Switzerland, serving the eastern part of the city near the Olympic Museum and local residential areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vennes
Target entity description: Vennes is a metro station on Lausanne’s M2 line in Switzerland, serving the eastern part of the city near the Olympic Museum and local residential areas.
  • A. Verran
    Verran is a former municipality in Trøndelag county, Norway, known for its rural landscapes, forestry, and fjord-side settlements.
  • B. Vennachar
    Vennachar is a small rural community located within the township of Addington Highlands in eastern Ontario, Canada.
  • C. Villeneuviens
    Villeneuviens are the inhabitants of the French commune of Villeneuve-sur-Yonne in the Yonne department of Bourgogne-Franche-Comté.
  • D. Veniste
    Veniste is a component or subdivision associated with Ben-Veniste, likely representing a related name, branch, or derivative entity.
  • E. Vestnes
    Vestnes is a municipality and village in western Norway known for its coastal location along the Romsdalsfjord and its role as a local administrative and service center.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03686bfb8819080ba0caae652170a completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feef8513a08190b2d2a7dde85dd43d completed May 9, 2026, 8:25 a.m.
NEDg Description generation batch_69fef23de4688190beeb59ef43891e3d completed May 9, 2026, 8:37 a.m.
NED2 Entity disambiguation (via description) batch_69fef2d8fe04819084bb3deb6859d746 completed May 9, 2026, 8:39 a.m.
Created at: April 10, 2026, 3:15 a.m.