Triple

T24137445
Position Surface form Disambiguated ID Type / Status
Subject Skokloster Church E598127 entity
Predicate associatedWith P37 FINISHED
Object Skokloster parish
Skokloster parish is a Church of Sweden parish in Uppsala County, Sweden, centered around the historic Skokloster Church and serving the local Skokloster community.
E1621533 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: Skokloster parish | Statement: [Skokloster Church, associatedWith, Skokloster parish]
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: Skokloster parish
Triple: [Skokloster Church, associatedWith, Skokloster parish]
Generated description
Skokloster parish is a Church of Sweden parish in Uppsala County, Sweden, centered around the historic Skokloster Church and serving the local Skokloster community.

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_69e288c92e448190ac57034fa0c863ce completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1df7d30a0819092ecea0cf58c2332 completed April 29, 2026, 10:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad23854c8190b71971401d3cb42a completed May 22, 2026, 1:10 a.m.
NEDg Description generation batch_6a0fae49d6a08190b20305c2e8199b80 completed May 22, 2026, 1:15 a.m.
NED2 Entity disambiguation (via description) batch_6a0faf52f7508190ba5ca0d7123f6619 completed May 22, 2026, 1:20 a.m.
Created at: April 17, 2026, 11:27 p.m.