Triple

T10192157
Position Surface form Disambiguated ID Type / Status
Subject Erik Møse E238062 entity
Predicate familyName P18 FINISHED
Object Møse
Møse is a Norwegian surname most notably borne by Erik Møse, a prominent jurist and international judge.
E847243 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: Møse | Statement: [Erik Møse, familyName, Møse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Møse
Context triple: [Erik Møse, familyName, Møse]
  • A. Snogebæk
    Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
  • B. Strømsø
    Strømsø is a historic district and former separate town that now forms part of the city of Drammen in Norway.
  • C. Vangsmjøse
    Vangsmjøse is a lake in the Valdres region of Innlandet county, Norway, known for its scenic mountain surroundings and clear waters.
  • D. Tjøme
    Tjøme is a scenic island and former municipality in Vestfold, Norway, known for its coastal landscapes, summer cabins, and popular seaside recreation areas.
  • E. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • 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: Møse
Triple: [Erik Møse, familyName, Møse]
Generated description
Møse is a Norwegian surname most notably borne by Erik Møse, a prominent jurist and international judge.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Møse
Target entity description: Møse is a Norwegian surname most notably borne by Erik Møse, a prominent jurist and international judge.
  • A. Snogebæk
    Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
  • B. Strømsø
    Strømsø is a historic district and former separate town that now forms part of the city of Drammen in Norway.
  • C. Vangsmjøse
    Vangsmjøse is a lake in the Valdres region of Innlandet county, Norway, known for its scenic mountain surroundings and clear waters.
  • D. Tjøme
    Tjøme is a scenic island and former municipality in Vestfold, Norway, known for its coastal landscapes, summer cabins, and popular seaside recreation areas.
  • E. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • 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_69ca84de1b208190bf17bb305b002605 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdedc4fb808190aae2e4b84be96f83 completed April 2, 2026, 4:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d317ca2cf481909cf715ef9248be3c completed April 6, 2026, 2:17 a.m.
NEDg Description generation batch_69d3188886908190ba0a5539ce942980 completed April 6, 2026, 2:20 a.m.
NED2 Entity disambiguation (via description) batch_69d31c4fb8288190bbc6b3d4a79dafb1 completed April 6, 2026, 2:37 a.m.
Created at: March 30, 2026, 9:13 p.m.