Triple

T12852945
Position Surface form Disambiguated ID Type / Status
Subject Marija Milošević E307369 entity
Predicate countryOfCitizenship P2 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: [Marija Milošević, countryOfCitizenship, Serbia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serbia
Context triple: [Marija Milošević, countryOfCitizenship, 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97021df7481909cd42a0f72040aa5 completed April 10, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbb735e481909f120f95fa68f4f1 completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 5:36 p.m.