Triple

T32548878
Position Surface form Disambiguated ID Type / Status
Subject Vinje E831920 entity
Predicate hasCulturalInstitution P105 FINISHED
Object Telemarkstunet at Rauland
Telemarkstunet at Rauland is a traditional cultural farmstead and visitor center in Vinje, Norway, showcasing Telemark’s folk architecture, crafts, and rural heritage.
E2011460 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: Telemarkstunet at Rauland | Statement: [Vinje, hasCulturalInstitution, Telemarkstunet at Rauland]
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: Telemarkstunet at Rauland
Triple: [Vinje, hasCulturalInstitution, Telemarkstunet at Rauland]
Generated description
Telemarkstunet at Rauland is a traditional cultural farmstead and visitor center in Vinje, Norway, showcasing Telemark’s folk architecture, crafts, and rural heritage.

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_69f34925fd08819084cfe4ec566cb704 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c5c3636c81908cb7b9418c47dbf0 completed May 3, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a347b887f148190875ba8b7948d1f4e completed June 18, 2026, 11:13 p.m.
NEDg Description generation batch_6a347c67712081908c1641c46b1abc0c completed June 18, 2026, 11:16 p.m.
NED2 Entity disambiguation (via description) batch_6a347cebd4f08190856060b0b27e2186 completed June 18, 2026, 11:19 p.m.
Created at: May 1, 2026, 1:02 a.m.