Triple

T4857705
Position Surface form Disambiguated ID Type / Status
Subject Aleksandra Dulkiewicz E108576 entity
Predicate name P16 FINISHED
Object Aleksandra Dulkiewicz E108576 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: Aleksandra Dulkiewicz | Statement: [Aleksandra Dulkiewicz, name, Aleksandra Dulkiewicz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aleksandra Dulkiewicz
Context triple: [Aleksandra Dulkiewicz, name, Aleksandra Dulkiewicz]
  • A. Aleksandra Dulkiewicz chosen
    Aleksandra Dulkiewicz is a Polish lawyer and politician who serves as the mayor of Gdańsk, known for her pro-European stance and advocacy of democratic values.
  • B. Agata Kornhauser-Duda
    Agata Kornhauser-Duda is a Polish teacher and the First Lady of Poland, known for her role as the wife of President Andrzej Duda.
  • C. Maria Jankowska
    Maria Jankowska was a Polish political activist known for her pioneering role in the early socialist movement in Poland.
  • D. Ewelina Hańska
    Ewelina Hańska was a Polish noblewoman best known as the longtime correspondent, muse, and eventually wife of French novelist Honoré de Balzac.
  • E. Monika Lenczewska
    Monika Lenczewska is a Polish cinematographer known for her visually striking work on international films and television projects.
  • 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_69bd440a89548190a5f14ba6da6b97dc completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d3f24688190b2f2b79bcde96973 completed March 20, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67dd3df4819092a59dfb85d10683 completed March 21, 2026, 9:41 a.m.
Created at: March 20, 2026, 1:26 p.m.