Triple

T18005223
Position Surface form Disambiguated ID Type / Status
Subject Ministerstwo Obrony Narodowej E430728 entity
Predicate country P26 FINISHED
Object Polska 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: Polska | Statement: [Ministerstwo Obrony Narodowej, country, Polska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Polska
Context triple: [Ministerstwo Obrony Narodowej, country, Polska]
  • A. Polonia
    Polonia refers to the global community of people of Polish origin living outside Poland, encompassing their cultural, social, and political organizations worldwide.
  • B. Poland chosen
    Poland is a Central European country known for its rich medieval heritage, resilient culture, and pivotal role in 20th-century history, including being the site of the outbreak of World War II.
  • C. Polón
    Polón is a Finnish surname most notably associated with Eduard Polón, an industrialist and co-founder of the company that became part of Nokia.
  • D. Polenovo
    Polenovo is a historic artist’s estate and museum complex in Russia, best known as the country home and creative workshop of painter Vasily Polenov.
  • E. Franuś
    Franuś is a Polish diminutive form of the male given name Franciszek, used as an affectionate or familiar nickname.
  • 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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b51ba1888190a339d726e92f376b completed April 19, 2026, 10:57 a.m.
Created at: April 10, 2026, 10:24 a.m.