Triple

T16037757
Position Surface form Disambiguated ID Type / Status
Subject Svetlana Alexievich E389011 entity
Predicate citizenship P2 FINISHED
Object Belarus E13665 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: Belarus | Statement: [Svetlana Alexievich, citizenship, Belarus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belarus
Context triple: [Svetlana Alexievich, citizenship, Belarus]
  • A. Belarus chosen
    Belarus is an Eastern European country known for its flat landscapes, dense forests, and historical ties to both the Soviet Union and the broader Slavic cultural sphere.
  • B. Belarus–Russia
    Belarus–Russia refers to the shared border area and bilateral relationship between the Republic of Belarus and the Russian Federation, encompassing close political, economic, and cultural ties.
  • C. Belarus and Latvia
    Belarus and Latvia are neighboring Eastern European countries that were selected to jointly host the 2021 IIHF Ice Hockey World Championship.
  • D. Belarus–Poland
    Belarus–Poland refers to the international border region where Belarus and Poland meet, encompassing shared historical, cultural, and ecological landscapes.
  • E. Belorusskaya
    Belorusskaya is a Moscow Metro station that serves as a key transport hub and interchange point near Belorussky railway terminal.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1833da68881908710fb2c28e8c6d0 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff293c2248190993d5d74eaf626bc completed May 10, 2026, 2:50 a.m.
Created at: April 10, 2026, 4:56 a.m.