Triple

T25102152
Position Surface form Disambiguated ID Type / Status
Subject Deventer station E628756 entity
Predicate railwayLine P848 FINISHED
Object Deventer–Almelo railway
The Deventer–Almelo railway is a rail line in the eastern Netherlands that connects the cities of Deventer and Almelo as part of the national railway network.
 E1765580 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: Deventer–Almelo railway | Statement: [Deventer station, railwayLine, Deventer–Almelo railway]
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: Deventer–Almelo railway
Triple: [Deventer station, railwayLine, Deventer–Almelo railway]
Generated description
The Deventer–Almelo railway is a rail line in the eastern Netherlands that connects the cities of Deventer and Almelo as part of the national railway network.

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_69e2ff3071548190b62d1ac237397197 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f464be45448190b42c7d880d8550c8 completed May 1, 2026, 8:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a129c750e048190bfc69cedb6ebbd7c completed May 24, 2026, 6:36 a.m.
NEDg Description generation batch_6a129d440e448190bad8b3e249c41698 completed May 24, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_6a129dac5d2081908e48a30357a8547f completed May 24, 2026, 6:41 a.m.
Created at: April 18, 2026, 6:26 a.m.