Triple

T5378149
Position Surface form Disambiguated ID Type / Status
Subject Eastern and Central Europe E113011 entity
Predicate hasCountry P846 FINISHED
Object Serbia E26132 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: Serbia | Statement: [Eastern and Central Europe, hasCountry, Serbia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serbia
Context triple: [Eastern and Central Europe, hasCountry, Serbia]
  • A. Serbia chosen
    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.
  • B. Serbja
    Serbja are a West Slavic ethnic minority primarily living in eastern Germany, known for their distinct Sorbian language and culture.
  • C. Servia
    Servia is a town in northern Greece located in the Kozani regional unit of Western Macedonia.
  • D. Serbia and Montenegro
    Serbia and Montenegro was a former state union in the Balkans, comprising the republics of Serbia and Montenegro, that existed from 2003 until Montenegro’s 2006 declaration of independence.
  • E. Serbia and Bulgaria
    Serbia and Bulgaria are neighboring Balkan countries in Southeast Europe whose modern boundary was shaped by early 20th-century conflicts and diplomatic agreements.
  • 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_69bd4436a1988190af18dcff7fd306b4 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd86cb13ac81909dc364e7d3605844 completed March 20, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf29193b6c8190bbf0854b4a766009 completed March 21, 2026, 11:26 p.m.
Created at: March 20, 2026, 2:03 p.m.