Triple

T33768899
Position Surface form Disambiguated ID Type / Status
Subject Jakob Oftebro E865318 entity
Predicate hasRelative P367 FINISHED
Object Nils Ole Oftebro
Nils Ole Oftebro is a Norwegian actor known for his extensive work in film, television, and theatre since the 1970s.
E2236244 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: Nils Ole Oftebro | Statement: [Jakob Oftebro, hasRelative, Nils Ole Oftebro]
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: Nils Ole Oftebro
Triple: [Jakob Oftebro, hasRelative, Nils Ole Oftebro]
Generated description
Nils Ole Oftebro is a Norwegian actor known for his extensive work in film, television, and theatre since the 1970s.

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_69f3498df6f88190bf9647ea4e4a956e completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fc908760819099453c8d3b62cf55 completed May 3, 2026, 7:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a40afc2f03c81908f95428aa7c0465a completed June 28, 2026, 5:23 a.m.
NEDg Description generation batch_6a40b157330481908cb84a6b23ab2ea8 completed June 28, 2026, 5:29 a.m.
NED2 Entity disambiguation (via description) batch_6a40b1e7df4c8190a7f52452a2bdf288 completed June 28, 2026, 5:32 a.m.
Created at: May 1, 2026, 1:45 a.m.