Triple

T15302450
Position Surface form Disambiguated ID Type / Status
Subject Viking FK E365821 entity
Predicate manager P2962 FINISHED
Object Morten Jensen
Morten Jensen is a Norwegian football coach best known for managing top-flight club Viking FK.
E1170038 NE FINISHED

How this triple was built (4 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: Morten Jensen | Statement: [Viking FK, manager, Morten Jensen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morten Jensen
Context triple: [Viking FK, manager, Morten Jensen]
  • A. Morten Rasmussen
    Morten Rasmussen is a Danish former professional footballer known for his prolific goal-scoring as a striker, particularly in the Danish Superliga.
  • B. Niels Jensen
    Niels Jensen is a software entrepreneur best known as one of the founders of the software company Borland.
  • C. Morten Borg
    Morten Borg is a Norwegian figure known primarily as the father of Marius Borg Høiby, the eldest son of Norway’s Crown Princess Mette-Marit.
  • D. Morten Sidek
    Morten Sidek is a member of Malaysia’s renowned Sidek badminton family and the brother of legendary coach and player Misbun Sidek.
  • E. Terje Hansen
    Terje Hansen is an academic author known for co-authoring scholarly work with prominent economist and mathematician Herbert Scarf.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Morten Jensen
Triple: [Viking FK, manager, Morten Jensen]
Generated description
Morten Jensen is a Norwegian football coach best known for managing top-flight club Viking FK.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Morten Jensen
Target entity description: Morten Jensen is a Norwegian football coach best known for managing top-flight club Viking FK.
  • A. Morten Rasmussen
    Morten Rasmussen is a Danish former professional footballer known for his prolific goal-scoring as a striker, particularly in the Danish Superliga.
  • B. Niels Jensen
    Niels Jensen is a software entrepreneur best known as one of the founders of the software company Borland.
  • C. Morten Borg
    Morten Borg is a Norwegian figure known primarily as the father of Marius Borg Høiby, the eldest son of Norway’s Crown Princess Mette-Marit.
  • D. Morten Sidek
    Morten Sidek is a member of Malaysia’s renowned Sidek badminton family and the brother of legendary coach and player Misbun Sidek.
  • E. Terje Hansen
    Terje Hansen is an academic author known for co-authoring scholarly work with prominent economist and mathematician Herbert Scarf.
  • F. None of above. chosen

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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03ccd575c8190aa43262d3b73ef3c completed April 16, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff677d34748190b5f723b5fd18b3a0 completed May 9, 2026, 4:57 p.m.
NEDg Description generation batch_69ff6856260c8190b82b40c484f87211 completed May 9, 2026, 5:01 p.m.
NED2 Entity disambiguation (via description) batch_69ff68e8e2c08190b460e23fe24f05e9 completed May 9, 2026, 5:03 p.m.
Created at: April 10, 2026, 3:15 a.m.