Triple

T6873114
Position Surface form Disambiguated ID Type / Status
Subject Dagmar of Denmark E158600 entity
Predicate givenName P17 FINISHED
Object Dagmar E99835 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: Dagmar | Statement: [Dagmar of Denmark, givenName, Dagmar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dagmar
Context triple: [Dagmar of Denmark, givenName, Dagmar]
  • A. Dagmar chosen
    Dagmar is a feminine given name of Germanic origin, historically associated with European nobility and still used in various countries today.
  • B. Hedvig
    Hedvig is a Scandinavian female given name, historically borne by several notable women in Swedish and broader Nordic royalty and nobility.
  • C. Florence Dagmar
    Florence Dagmar was an early 20th-century American silent film actress known for her roles in dramas of the 1910s.
  • D. Ulrike
    Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
  • E. Dagmar of Denmark
    Dagmar of Denmark, later known as Empress Maria Feodorovna, was a Danish princess who became Empress consort of Russia as the wife of Tsar Alexander III and mother of the last Russian tsar, Nicholas II.
  • 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_69c68832af1481908ce356e133ebaebe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8c73ea08190b6bb1463e7ead47b completed March 27, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c742af0df88190bb23b7495c279e08 completed March 28, 2026, 2:53 a.m.
Created at: March 27, 2026, 2:22 p.m.