Triple

T4463921
Position Surface form Disambiguated ID Type / Status
Subject Margrete E98326 entity
Predicate hasCognate P2525 FINISHED
Object Margareta E113357 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: Margareta | Statement: [Margrete, hasCognate, Margareta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margareta
Context triple: [Margrete, hasCognate, Margareta]
  • A. Margareta chosen
    Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
  • B. Agneta
    Agneta is a feminine given name, primarily used in Scandinavian countries, that is a variant of the name Agnes.
  • C. Violanta
    Violanta is a one-act opera by Erich Wolfgang Korngold, known for its lush late-Romantic score and psychologically intense drama set in Renaissance Venice.
  • D. Gisela
    Gisela was a daughter of Charlemagne, the Frankish king and first Holy Roman Emperor, and a member of the Carolingian royal family.
  • E. Hedvig
    Hedvig is a Scandinavian female given name, historically borne by several notable women in Swedish and broader Nordic royalty and nobility.
  • 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_69b3454a7c608190944f5455c8031d73 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3567913788190ac4f28fbe63a4fa9 completed March 13, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6285164b081908f144e74ae3a1be8 completed March 15, 2026, 3:32 a.m.
Created at: March 12, 2026, 11:34 p.m.