Triple

T489264
Position Surface form Disambiguated ID Type / Status
Subject Bulgaria E9949 entity
Predicate capital P234 FINISHED
Object Sofia E31299 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: Sofia | Statement: [Bulgaria, capital, Sofia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sofia
Context triple: [Bulgaria, capital, Sofia]
  • A. Sofia chosen
    Sofia is the capital and largest city of Bulgaria, known as a major cultural, economic, and historical center in the Balkans.
  • B. Varna
    Varna is a major Bulgarian city on the Black Sea coast known as an important economic, cultural, and maritime center.
  • C. Bucharest
    Bucharest is the capital and largest city of Romania, known for its mix of historic architecture, wide boulevards, and its role as the country’s political, cultural, and economic center.
  • D. Belgrade
    Belgrade is the capital and largest city of Serbia, historically significant as a strategic crossroads between Central Europe and the Balkans on the confluence of the Sava and Danube rivers.
  • E. Burgas
    Burgas is a major Bulgarian city and industrial center on the Black Sea coast, known for its large seaport and role as a key maritime and logistics hub in the region.
  • 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_69a2e802e2908190ab17c9479e0b6412 completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f0e0a9648190b6a3b2da3a3b51e6 completed Feb. 28, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e9b6d1088190a925b1b3d78e9674 completed March 2, 2026, 1:36 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.