Triple

T13965167
Position Surface form Disambiguated ID Type / Status
Subject Gitte Nielsen E335903 entity
Predicate familyName P18 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: [Gitte Nielsen, familyName, Nielsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nielsen
Context triple: [Gitte Nielsen, familyName, 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. Nielsen Company
    Nielsen Company is a global measurement and data analytics firm best known for providing audience and consumer insights across media, entertainment, and retail industries.
  • D. Kantar (historically)
    Kantar is a major global data, insights, and consulting company that was historically owned by the advertising and communications group WPP plc.
  • E. Gallup
    Gallup is a small city in northwestern New Mexico known as a historic stop along Route 66 and a cultural center for Native American art and trading.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e7e24f08190ba939a8044860033 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1d890d48190affd194b2439c271 completed May 6, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:18 p.m.