Triple

T315936
Position Surface form Disambiguated ID Type / Status
Subject Kutaisi E7705 entity
Predicate hasSisterCity P919 FINISHED
Object Brest E16888 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: Brest | Statement: [Kutaisi, hasSisterCity, Brest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brest
Context triple: [Kutaisi, hasSisterCity, Brest]
  • A. Białystok
    Białystok is a city in northeastern Poland best known as the birthplace of L. L. Zamenhof and the cradle of the international language Esperanto.
  • B. Wilno
    Wilno is the historical Polish name for Vilnius, a major cultural and political center of the region that served as an important city in the interwar Second Polish Republic.
  • C. Königsberg
    Königsberg was a historic Prussian city on the Baltic Sea, renowned as a major cultural and intellectual center of East Prussia and later known as Kaliningrad.
  • D. Vitebsk chosen
    Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
  • E. Warsaw
    Warsaw is the capital and largest city of Poland, known for its resilient history, especially its near-total destruction in World War II and subsequent postwar reconstruction.
  • 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_69a2e7e7af7881908890039d6be4e9b8 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ea6462148190825acc57f6d2adaf completed Feb. 28, 2026, 1:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3c41c00888190861d2b6d4bfc8904 completed March 1, 2026, 4:44 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.