Triple

T19173460
Position Surface form Disambiguated ID Type / Status
Subject Saint Petersburg Moskovsky railway station E469382 entity
Predicate connectsWith P37 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: [Saint Petersburg Moskovsky railway station, connectsWith, Minsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Minsk
Context triple: [Saint Petersburg Moskovsky railway station, connectsWith, 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f16613dc8190987c2d79dc616e40 completed April 20, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a070e5f469881908d9a3e82337e92af completed May 15, 2026, 12:15 p.m.
Created at: April 10, 2026, 12:06 p.m.