Triple

T1963378
Position Surface form Disambiguated ID Type / Status
Subject Monika Mann E42635 entity
Predicate givenName P17 FINISHED
Object Monika E42635 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: Monika | Statement: [Monika Mann, givenName, Monika]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monika
Context triple: [Monika Mann, givenName, Monika]
  • A. Monika Mann chosen
    Monika Mann was a German writer and essayist, best known as one of the literary Nobel laureate Thomas Mann’s daughters and a member of the prominent Mann family of intellectuals.
  • B. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • C. Katia
    Katia is the Atlantic hurricane name that was introduced to replace the retired name Katrina following the devastating 2005 storm.
  • D. Felicia
    Felicia is a feminine given name of Latin origin meaning "happy" or "fortunate," used in various cultures around the world.
  • E. Veronika
    Veronika is the troubled young protagonist of Paulo Coelho's novel "Veronika Decides to Die," whose suicide attempt leads her to a transformative stay in a mental institution.
  • 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_69a88711151c8190940b2572095059d7 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3ac31a08190abaecac8badc52c7 completed March 7, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae031ef4e48190af93dfd6f33184d3 completed March 8, 2026, 11:15 p.m.
Created at: March 4, 2026, 7:36 p.m.