Triple

T35532810
Position Surface form Disambiguated ID Type / Status
Subject Moskenes Municipality E1026847 entity
Predicate governingBody P46 FINISHED
Object Moskenes municipal council
Moskenes municipal council is the elected local governing body responsible for making political and administrative decisions for the municipality of Moskenes in Norway.
E2144466 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: Moskenes municipal council | Statement: [Moskenes Municipality, governingBody, Moskenes 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: Moskenes municipal council
Triple: [Moskenes Municipality, governingBody, Moskenes municipal council]
Generated description
Moskenes municipal council is the elected local governing body responsible for making political and administrative decisions for the municipality of Moskenes in 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_69f76dff7e508190b28ceeee770dce23 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f797d2da188190813233b0489cf62d completed May 3, 2026, 6:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a384a4b03088190b93a018bc93b53c8 completed June 21, 2026, 8:32 p.m.
NEDg Description generation batch_6a384b14247c81909c691fbbfad22c79 completed June 21, 2026, 8:35 p.m.
NED2 Entity disambiguation (via description) batch_6a384b9c09d88190afb8dc6aeb098dbe completed June 21, 2026, 8:37 p.m.
Created at: May 3, 2026, 4:04 p.m.