Triple

T35909670
Position Surface form Disambiguated ID Type / Status
Subject Vågan E1038570 entity
Predicate governedBy P46 FINISHED
Object Vågan municipal council
Vågan municipal council is the elected local governing body responsible for making political and administrative decisions for the municipality of Vågan in Nordland, Norway.
E2161745 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: Vågan municipal council | Statement: [Vågan, governedBy, Vågan municipal council]
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: Vågan municipal council
Triple: [Vågan, governedBy, Vågan municipal council]
Generated description
Vågan municipal council is the elected local governing body responsible for making political and administrative decisions for the municipality of Vågan in Nordland, Norway.

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_69f76e2259608190bf6788a132e0d139 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa71a66c81909dba6a2c3466284c completed May 3, 2026, 8:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ae2b4d5c8190ac0caa7f3ece9b11 completed June 22, 2026, 3:38 a.m.
NEDg Description generation batch_6a38aed9c3608190be4d8a738722fc4f completed June 22, 2026, 3:41 a.m.
NED2 Entity disambiguation (via description) batch_6a38afe3882c819094065a02436b8868 completed June 22, 2026, 3:45 a.m.
Created at: May 3, 2026, 4:07 p.m.