Triple

T34974900
Position Surface form Disambiguated ID Type / Status
Subject Aust-Nedenes prosti E1008649 entity
Predicate regionServed P82 FINISHED
Object Aust-Nedenes
Aust-Nedenes is a historical district in southern Norway that formed part of the traditional county of Aust-Agder.
E2120906 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: Aust-Nedenes | Statement: [Aust-Nedenes prosti, regionServed, Aust-Nedenes]
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: Aust-Nedenes
Triple: [Aust-Nedenes prosti, regionServed, Aust-Nedenes]
Generated description
Aust-Nedenes is a historical district in southern Norway that formed part of the traditional county of Aust-Agder.

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_69f76dc78a308190a1ac29ad4a9a4895 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7846678808190b0f6e3286f82bb0c completed May 3, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37b279f00c8190b9b740e964ff217d completed June 21, 2026, 9:44 a.m.
NEDg Description generation batch_6a37b3c955c88190989d0c2404a72ed1 completed June 21, 2026, 9:50 a.m.
NED2 Entity disambiguation (via description) batch_6a37b51173808190a8314a275b7c87d7 completed June 21, 2026, 9:55 a.m.
Created at: May 3, 2026, 4:01 p.m.