Triple

T543065
Position Surface form Disambiguated ID Type / Status
Subject Nilsen E12672 entity
Predicate hasEtymologicalRelation P5801 FINISHED
Object Nielsen E25294 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: Nielsen | Statement: [Nilsen, hasEtymologicalRelation, Nielsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nielsen
Context triple: [Nilsen, hasEtymologicalRelation, Nielsen]
  • A. Nielsen chosen
    Nielsen is a common Scandinavian surname, particularly prevalent in Denmark and Norway, traditionally meaning "son of Niels."
  • B. Nielson
    Nielson is a surname and given name that functions as a spelling variant of Nelson, commonly of Scandinavian or English origin.
  • C. Bomis
    Bomis was an early web portal and search engine company co-founded by Jimmy Wales that later played a key role in funding and incubating Wikipedia.
  • D. Luminate Data
    Luminate Data is a music and entertainment data analytics company that tracks and reports industry metrics such as sales, streaming, and airplay used to compile major charts.
  • E. NAB
    NAB is the commonly used abbreviation for the New American Bible, a Catholic English translation of the Bible widely used in the United States.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d278cf88190ad1368da91a7014f completed March 1, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4cc5f6dfc8190a6c97a81aa8e82a3 completed March 1, 2026, 11:31 p.m.
Created at: March 1, 2026, 7:32 p.m.