Triple

T789913
Position Surface form Disambiguated ID Type / Status
Subject Vitebsk E16888 entity
Predicate hasRailConnectionTo P848 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: [Vitebsk, hasRailConnectionTo, Minsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Minsk
Context triple: [Vitebsk, hasRailConnectionTo, 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. Vitebsk
    Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
  • E. Hrodna
    Hrodna is a historic city in western Belarus known for its well-preserved architecture and role as a major cultural and economic 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a7841b0c8190859ecd247e32c6ec completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3afbb0c8190b4e7aa7824c8b787 completed March 4, 2026, 3:14 a.m.
Created at: March 1, 2026, 7:38 p.m.