Triple

T34799641
Position Surface form Disambiguated ID Type / Status
Subject Aarberg railway station E1003181 entity
Predicate railwayLine P848 FINISHED
Object Lyss–Payerne railway line
The Lyss–Payerne railway line is a standard-gauge Swiss railway route in the canton of Bern that connects the towns of Lyss and Payerne, serving regional passenger and freight traffic.
E2112931 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: Lyss–Payerne railway line | Statement: [Aarberg railway station, railwayLine, Lyss–Payerne railway line]
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: Lyss–Payerne railway line
Triple: [Aarberg railway station, railwayLine, Lyss–Payerne railway line]
Generated description
The Lyss–Payerne railway line is a standard-gauge Swiss railway route in the canton of Bern that connects the towns of Lyss and Payerne, serving regional passenger and freight traffic.

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_69f76db543808190b188c6c86a91491b completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77a886ac48190a82b0a71a2092028 completed May 3, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a376fa9e7dc8190943192fe85c15ab5 completed June 21, 2026, 4:59 a.m.
NEDg Description generation batch_6a3770687b8c8190b271515f54eed3b8 completed June 21, 2026, 5:02 a.m.
NED2 Entity disambiguation (via description) batch_6a37719bed38819094df932b534a7b6a completed June 21, 2026, 5:07 a.m.
Created at: May 3, 2026, 3:59 p.m.