Triple

T33709283
Position Surface form Disambiguated ID Type / Status
Subject Kungälv Municipality E863686 entity
Predicate borderedBy P224 FINISHED
Object Öckerö Municipality
Öckerö Municipality is a coastal municipality in Västra Götaland County, Sweden, consisting of a group of islands in the northern Gothenburg archipelago.
E2088797 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: Öckerö Municipality | Statement: [Kungälv Municipality, borderedBy, Öckerö Municipality]
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: Öckerö Municipality
Triple: [Kungälv Municipality, borderedBy, Öckerö Municipality]
Generated description
Öckerö Municipality is a coastal municipality in Västra Götaland County, Sweden, consisting of a group of islands in the northern Gothenburg archipelago.

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_69f3498844608190bb8f9b14908d2510 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fab9ec108190a6879dcc45020aeb completed May 3, 2026, 7:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36e6048cbc8190998dba12a0f6019b completed June 20, 2026, 7:12 p.m.
NEDg Description generation batch_6a36e8413ddc8190b80406d6a133e849 completed June 20, 2026, 7:21 p.m.
NED2 Entity disambiguation (via description) batch_6a36e8d2a5888190b17c1bcb890c90df completed June 20, 2026, 7:24 p.m.
Created at: May 1, 2026, 1:43 a.m.