Triple

T8625544
Position Surface form Disambiguated ID Type / Status
Subject Earth (1930 film) E204271 entity
Predicate setIn P1393 FINISHED
Object Ukraine E14078 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: Ukraine | Statement: [Earth (1930 film), setIn, Ukraine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ukraine
Context triple: [Earth (1930 film), setIn, 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 (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_69ca834a4ea0819094970dceb9e389f3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc472a07908190a2368975459543f9 completed March 31, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebb9ef3ac819098810294e6bc34a7 completed April 2, 2026, 6:55 p.m.
Created at: March 30, 2026, 6:26 p.m.