Triple

T18652577
Position Surface form Disambiguated ID Type / Status
Subject Zhuliany Airport E455977 entity
Predicate hasCountry P846 FINISHED
Object Ukraine 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: Ukraine | Statement: [Zhuliany Airport, hasCountry, Ukraine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ukraine
Context triple: [Zhuliany Airport, hasCountry, Ukraine]
  • A. Ukraine chosen
    Ukraine is a large Eastern European country known for its fertile plains, strategic geopolitical position between Russia and the European Union, and its complex 20th- and 21st-century history marked by independence struggles and ongoing conflict.
  • B. Ukrainka
    Ukrainka is a small city in northern Ukraine situated along the Dnipro River within the Kyiv metropolitan area.
  • C. Ukraine and Moldova
    Ukraine and Moldova are neighboring Eastern European countries that share historical, cultural, and economic ties as well as a long land border.
  • D. Ukraine–Poland
    Ukraine–Poland refers to the shared border area and broader historical-cultural region linking Ukraine and Poland in Eastern Europe.
  • E. Romania and Ukraine
    Romania and Ukraine are neighboring Eastern European countries that share both land and river borders, including stretches along the Prut River.
  • 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_69d8d38ea1e88190997e9b231190ba6f completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5501279d08190aeca36df89fee2b2 completed April 19, 2026, 9:58 p.m.
Created at: April 10, 2026, 11:47 a.m.