Triple

T16860068
Position Surface form Disambiguated ID Type / Status
Subject Bunjevac E409886 entity
Predicate hasRegion P285 FINISHED
Object Hungary E5017 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: Hungary | Statement: [Bunjevac, hasRegion, Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hungary
Context triple: [Bunjevac, hasRegion, Hungary]
  • A. Hungary chosen
    Hungary is a landlocked Central European country known for its rich history, distinct language (Hungarian), and capital city Budapest, famed for its thermal baths and architecture.
  • B. Ungarie
    Ungarie is a small rural town in New South Wales, Australia, known for its agricultural community and location within the Bland Shire local government area.
  • C. Austria and Hungary
    Austria and Hungary are neighboring Central European countries with closely linked histories, cultures, and transportation networks.
  • D. Ungar
    Ungar is a surname of Germanic and Central European origin, historically associated with people from Hungary or of Hungarian descent.
  • E. Slovakia and Hungary
    Slovakia and Hungary are neighboring Central European countries that share a significant stretch of their border along the Danube 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b502bc048190baa5a83015407080 completed April 18, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb0adc408190a9cbfefdef8c669e completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:24 a.m.