Triple

T5581783
Position Surface form Disambiguated ID Type / Status
Subject Volksmarine E146656 entity
Predicate usedEquipmentFrom P4673 FINISHED
Object Poland 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: Poland | Statement: [Volksmarine, usedEquipmentFrom, Poland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Poland
Context triple: [Volksmarine, usedEquipmentFrom, Poland]
  • A. 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.
  • B. Polonia
    Polonia refers to the global community of people of Polish origin living outside Poland, encompassing their cultural, social, and political organizations worldwide.
  • 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. Lithuania
    Lithuania is a Baltic nation in Northern Europe known for its medieval history, restored independence from the Soviet Union in 1990, and membership in both the European Union and NATO.
  • E. Dzūkija
    Dzūkija is a historical ethnographic region in southeastern Lithuania known for its extensive forests, traditional rural culture, and distinctive dialect.
  • 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_69c0090287a08190b4098411effe970c completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0208147a48190b2cdb42b9c9814a3 completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027f2e98c8190880752c9ae8aba4f completed March 22, 2026, 5:33 p.m.
Created at: March 22, 2026, 3:37 p.m.