Triple

T27462158
Position Surface form Disambiguated ID Type / Status
Subject Enköping municipal council E692777 entity
Predicate locatedIn P40 FINISHED
Object Enköping Municipality
Enköping Municipality is a local government area in Uppsala County, Sweden, centered on the town of Enköping and responsible for providing municipal services and administration to its residents.
E187251 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: Enköping Municipality | Statement: [Enköping municipal council, locatedIn, Enköping 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: Enköping Municipality
Triple: [Enköping municipal council, locatedIn, Enköping Municipality]
Generated description
Enköping Municipality is a local government area in Uppsala County, Sweden, centered on the town of Enköping and responsible for providing municipal services and administration to its residents.

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_69ef5207903881909427745cda05d27a completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62dfa4f3881908a45c137df7fa0db completed May 2, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b86f2a28819086ea4d6973d95754 completed May 26, 2026, 3:12 p.m.
NEDg Description generation batch_6a15b930d3a48190b47c9a7921d3f9b5 completed May 26, 2026, 3:16 p.m.
NED2 Entity disambiguation (via description) batch_6a15bb82f47c8190bf0ec0ca187e3c4b completed May 26, 2026, 3:25 p.m.
Created at: April 27, 2026, 12:50 p.m.