Triple

T23781079
Position Surface form Disambiguated ID Type / Status
Subject Lausanne-Flon station E587813 entity
Predicate connectsTo P845 FINISHED
Object Lausanne city bus network
The Lausanne city bus network is the public transportation system of Lausanne, Switzerland, providing extensive bus services that connect the city’s neighborhoods with key transit hubs and surrounding areas.
E1601871 NE FINISHED

How this triple was built (2 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: Lausanne city bus network | Statement: [Lausanne-Flon station, connectsTo, Lausanne city bus network]
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: Lausanne city bus network
Triple: [Lausanne-Flon station, connectsTo, Lausanne city bus network]
Generated description
The Lausanne city bus network is the public transportation system of Lausanne, Switzerland, providing extensive bus services that connect the city’s neighborhoods with key transit hubs and surrounding areas.

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_69e2490d245881909028226a1393d624 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1c62bef608190b75afa6bf4024ae3 completed April 29, 2026, 8:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53e9b62c81908f82ae8ddcb56103 completed May 21, 2026, 6:50 p.m.
NEDg Description generation batch_6a0f57f957508190b2d5705854e5d989 completed May 21, 2026, 7:07 p.m.
NED2 Entity disambiguation (via description) batch_6a0f5899cd648190b4cc234933e0acf6 completed May 21, 2026, 7:10 p.m.
Created at: April 17, 2026, 7:16 p.m.