Triple

T20535580
Position Surface form Disambiguated ID Type / Status
Subject Margareta Gosebruch von Liechtenstern E504187 entity
Predicate givenName P17 FINISHED
Object Margareta 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: Margareta | Statement: [Margareta Gosebruch von Liechtenstern, givenName, Margareta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margareta
Context triple: [Margareta Gosebruch von Liechtenstern, givenName, 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. Brigitta
    Brigitta is a character based on one of the real-life von Trapp children, featured as one of the daughters in "The Sound of Music."
  • C. Maddalene
    Maddalene is a feminine given name, typically considered a variant of Maddalena or Magdalene, with roots in Christian and European naming traditions.
  • D. Anna Margareta
    Anna Margareta Tunder was a historical figure known primarily as the namesake and likely relative of the German Baroque composer and organist Franz Tunder.
  • E. Hjördis
    Hjördis is a Scandinavian feminine given name, most notably borne by Swedish model and actress Hjördis Genberg.
  • 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_69e0b4b476648190bc6019622ae54d3c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a06ed3088190bd01a95672b01ad6 completed April 20, 2026, 9:53 p.m.
Created at: April 16, 2026, 11:37 a.m.