Triple

T230201
Position Surface form Disambiguated ID Type / Status
Subject Balkans E4394 entity
Predicate hasCountry P846 FINISHED
Object Bulgaria E9949 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: Bulgaria | Statement: [Balkans, hasCountry, Bulgaria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bulgaria
Context triple: [Balkans, hasCountry, Bulgaria]
  • A. Bulgaria chosen
    Bulgaria is a Southeast European country on the Balkan Peninsula, known for its rich historical heritage, diverse landscapes, and role as a member of the European Union and NATO.
  • B. North Macedonia
    North Macedonia is a landlocked Balkan country in Southeast Europe known for its mountainous landscapes, rich cultural heritage, and recent integration into Euro-Atlantic institutions.
  • C. Romania
    Romania is a southeastern European country known for its role in World War II, its Carpathian mountain landscapes, and its historical regions such as Transylvania.
  • D. Serbia
    Serbia is a landlocked country in Southeast Europe, located in the central and western Balkans, known for its historical ties to Yugoslavia and its capital city, Belgrade.
  • E. Moldova
    Moldova is a landlocked Eastern European country situated between Romania and Ukraine, known for its wine production, agricultural economy, and post-Soviet political landscape.
  • 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_69a257363ffc81909757bde7ab3404da completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25cac7994819080b0b3b10808f8e5 completed Feb. 28, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69a5291da6c081908ebe0b83a8f3cfa0 completed March 2, 2026, 6:07 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.