Triple

T19096201
Position Surface form Disambiguated ID Type / Status
Subject Dabrowski E467411 entity
Predicate hasVariantSpelling P457 FINISHED
Object Dabrowsky 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: Dabrowsky | Statement: [Dabrowski, hasVariantSpelling, Dabrowsky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dabrowsky
Context triple: [Dabrowski, hasVariantSpelling, Dabrowsky]
  • A. Dabrowski chosen
    Dabrowski is a Polish surname, often spelled Dombrowski in variant forms, associated with numerous individuals of Polish origin or descent.
  • B. Björkman
    Björkman is a Swedish surname most notably associated with figures such as filmmaker and writer Stig Björkman.
  • C. Newcombe
    Newcombe is a surname of English origin borne by various notable individuals in fields such as sports, science, and public life.
  • D. Larcher
    Larcher is a French surname most notably borne by Gérard Larcher, a prominent French politician and long-serving President of the Senate.
  • E. Ebden
    Ebden is a rural locality and suburb within the City of Wodonga in northeastern Victoria, Australia, known for its proximity to Lake Hume and agricultural surroundings.
  • 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_69d8dd05ac4c8190b1967d8f97f3fb2f completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e368f20c8190bd84d2ba320991ac completed April 20, 2026, 8:27 a.m.
Created at: April 10, 2026, 12:04 p.m.