Triple

T21763434
Position Surface form Disambiguated ID Type / Status
Subject Robert Aske E537218 entity
Predicate familyName P18 FINISHED
Object Aske NE NERFINISHED

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: Aske | Statement: [Robert Aske, familyName, Aske]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aske
Context triple: [Robert Aske, familyName, Aske]
  • A. Aske chosen
    Aske is a surname of Scandinavian origin borne by various individuals, including those with the given name Ellen.
  • B. Asker
    Asker is a municipality in Viken county, Norway, known for its coastal location near Oslo and its mix of residential areas, cultural sites, and natural landscapes.
  • C. Askeran
    Askeran is a town in the disputed Nagorno-Karabakh region of the South Caucasus, historically known for its strategic location and fortress.
  • D. Andselv
    Andselv is a small Norwegian village located in the Troms region, known for its position along the Andselva river and proximity to Bardufoss.
  • E. Askvoll
    Askvoll is a coastal municipality and village area in western Norway known for its fjord landscape, fishing traditions, and proximity to the North Sea.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46f5d1c8190bf830409e98464e5 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f031a711dc8190a786c9849dc344e8 completed April 28, 2026, 4:03 a.m.
Created at: April 16, 2026, 6:51 p.m.