Triple

T16329334
Position Surface form Disambiguated ID Type / Status
Subject Agnieszka E396506 entity
Predicate hasVariant P455 FINISHED
Object Agnieszka (with diacritics unchanged) E396506 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: Agnieszka (with diacritics unchanged) | Statement: [Agnieszka, hasVariant, Agnieszka (with diacritics unchanged)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agnieszka (with diacritics unchanged)
Context triple: [Agnieszka, hasVariant, Agnieszka (with diacritics unchanged)]
  • A. Agnieszka chosen
    Agnieszka is a Polish feminine given name, commonly regarded as the Polish form of Agnes.
  • B. Grzymisława
    Grzymisława was a medieval noblewoman, known as Grzymisława of Łuck, associated with the ruling elites of the historical region of Volhynia in Eastern Europe.
  • C. Zuzanna
    Zuzanna is a feminine given name, primarily used in Slavic countries, that is a variant of the name Susanna.
  • D. Zofia
    Zofia is a feminine given name of Slavic origin, particularly common in Poland and other Central and Eastern European countries.
  • E. Ania
    Ania is a common Polish diminutive form of the female given name Anna, often used as an affectionate or familiar version of the name.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4ddc5608190b24fe2e871691470 completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002da915ac8190820acbe0db72c8a1 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:07 a.m.