Triple

T30737189
Position Surface form Disambiguated ID Type / Status
Subject Fredrik Skagen E782585 entity
Predicate notableWork P4 FINISHED
Object Kortslutning
Kortslutning is a crime novel by Norwegian author Fredrik Skagen, known for its suspenseful plot and psychological depth.
E1929741 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: Kortslutning | Statement: [Fredrik Skagen, notableWork, Kortslutning]
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: Kortslutning
Triple: [Fredrik Skagen, notableWork, Kortslutning]
Generated description
Kortslutning is a crime novel by Norwegian author Fredrik Skagen, known for its suspenseful plot and psychological depth.

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_69f224aeb1588190897d395e8ed2acb8 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68ee839988190a82465cf8061b712 completed May 2, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a289916104c8190beac825471534ca0 completed June 9, 2026, 10:52 p.m.
NEDg Description generation batch_6a2899f4a9488190a4ef4d96ec795595 completed June 9, 2026, 10:55 p.m.
NED2 Entity disambiguation (via description) batch_6a289ad47e94819094f1ea64c2804aa2 completed June 9, 2026, 10:59 p.m.
Created at: April 29, 2026, 8:37 p.m.