Triple

T15747593
Position Surface form Disambiguated ID Type / Status
Subject Informacja Wojskowa (we współpracy) E381759 entity
Predicate country P26 FINISHED
Object Polska E5029 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: Polska | Statement: [Informacja Wojskowa (we współpracy), country, Polska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Polska
Context triple: [Informacja Wojskowa (we współpracy), 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. Franuś
    Franuś is a Polish diminutive form of the male given name Franciszek, used as an affectionate or familiar nickname.
  • E. Polish Polesie
    Polish Polesie is the portion of the historic Polesia region that lies within modern Poland, characterized by its wetlands, forests, and traditional rural landscapes.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0502d72008190b4d13a6b3a12e467 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff876b7fd081909d84ebe7a4cdb675 completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 4:46 a.m.