Triple

T8393106
Position Surface form Disambiguated ID Type / Status
Subject Русины E197989 entity
Predicate проживаютВ P6481 FINISHED
Object Польша 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: Польша | Statement: [Русины, проживаютВ, Польша]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Польша
Context triple: [Русины, проживаютВ, Польша]
  • 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. Puolanka
    Puolanka is a small rural municipality in the Kainuu region of northern Finland, known for its scenic nature and self-deprecating “pessimism” tourism theme.
  • E. Poland and Czech Republic
    Poland and the Czech Republic are neighboring Central European countries known for their shared history, cultural ties, and extensive cross-border rail connections.
  • 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_69ca82f816bc8190ab321c07d72208c1 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cbd120a1ec8190a8dc101fa1371780 completed March 31, 2026, 1:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4da752488190be9bab1270182699 completed April 2, 2026, 11:06 a.m.
Created at: March 30, 2026, 6:03 p.m.