Triple

T11467906
Position Surface form Disambiguated ID Type / Status
Subject Olga Korbut E271823 entity
Predicate trainingLocation P40 FINISHED
Object Minsk E43503 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: Minsk | Statement: [Olga Korbut, trainingLocation, Minsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Minsk
Context triple: [Olga Korbut, trainingLocation, Minsk]
  • A. Minsk chosen
    Minsk is the capital and largest city of Belarus, serving as its political, economic, and cultural center.
  • B. Gomel
    Gomel is a major city in southeastern Belarus, serving as an important cultural, industrial, and economic center near the border with Russia and Ukraine.
  • C. Brest (Belarus)
    Brest is a city in southwestern Belarus near the Polish border, known as a major transport hub and for the historic Brest Fortress, a key World War II memorial.
  • D. Mogilev
    Mogilev is a major city in eastern Belarus known as an important industrial and cultural center on the Dnieper River.
  • E. Vilna
    Vilna is the historical name for Vilnius, the capital city of Lithuania and a major cultural and political center of 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f74144819094479690c8151073 completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e60415f6ac8190ad81ed0ef0a30e12 completed April 20, 2026, 10:46 a.m.
Created at: April 8, 2026, 9:35 p.m.