Triple

T23431739
Position Surface form Disambiguated ID Type / Status
Subject Agnieszka Nowak E563350 entity
Predicate hasGivenName P17 FINISHED
Object Agnieszka 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: Agnieszka | Statement: [Agnieszka Nowak, hasGivenName, Agnieszka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agnieszka
Context triple: [Agnieszka Nowak, hasGivenName, Agnieszka]
  • A. Agnieszka chosen
    Agnieszka is a Polish feminine given name, commonly regarded as the Polish form of Agnes.
  • B. Weronika
    Weronika is the enigmatic Polish woman whose mysterious emotional and spiritual connection to her French double, Véronique, forms the heart of Krzysztof Kieślowski’s film "The Double Life of Véronique."
  • C. Katarzyna
    Katarzyna is a common Polish female given name, equivalent to Catherine in English.
  • D. Zuzanna
    Zuzanna is a feminine given name, primarily used in Slavic countries, that is a variant of the name Susanna.
  • E. Dorota
    Dorota is a feminine given name used in various Slavic and European cultures, often considered a variant of Dorothy.
  • 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_69e24553980c8190bb66a2ae0bdab125 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a5d920548190904f80c7c40cba06 completed April 29, 2026, 6:31 a.m.
Created at: April 17, 2026, 5:49 p.m.