Triple

T32302816
Position Surface form Disambiguated ID Type / Status
Subject Ministry of Health and Social Affairs of Sweden E825279 entity
Predicate coordinatesWith P1140 FINISHED
Object county councils of Sweden
County councils of Sweden are regional self-governing authorities responsible primarily for healthcare and public transport within their respective counties.
E2002879 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: county councils of Sweden | Statement: [Ministry of Health and Social Affairs of Sweden, coordinatesWith, county councils of Sweden]
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: county councils of Sweden
Triple: [Ministry of Health and Social Affairs of Sweden, coordinatesWith, county councils of Sweden]
Generated description
County councils of Sweden are regional self-governing authorities responsible primarily for healthcare and public transport within their respective counties.

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_69f349115304819084ee91d345b6c8aa completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bd7ace288190bb6a6b2b300bbd88 completed May 3, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a30570cfd888190bfadf79c4cfcdb9b completed June 15, 2026, 7:48 p.m.
NEDg Description generation batch_6a31b9a482308190a82183f8bf571854 completed June 16, 2026, 9:01 p.m.
NED2 Entity disambiguation (via description) batch_6a33e21b231c8190860a4633feccc7fb completed June 18, 2026, 12:18 p.m.
Created at: May 1, 2026, 12:45 a.m.