Triple

T20331888
Position Surface form Disambiguated ID Type / Status
Subject Moscow–Minsk railway E492502 entity
Predicate passesThrough P225 FINISHED
Object Smolensk NE NERFINISHED

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: Smolensk | Statement: [Moscow–Minsk railway, passesThrough, Smolensk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Smolensk
Context triple: [Moscow–Minsk railway, passesThrough, Smolensk]
  • A. Smolensk chosen
    Smolensk is a historic city in western Russia near the Belarusian border, known for its strategic location and centuries-old fortifications.
  • B. Podolsk
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • C. Smolenskaya
    Smolenskaya is a Moscow Metro station on the Arbatsko–Pokrovskaya and Filyovskaya lines, located near the historic Arbat district.
  • D. Borisoglebsk
    Borisoglebsk is a small Russian city known for its historical architecture and location on the Vorona River in southwestern Russia.
  • E. Trubchevsk
    Trubchevsk is a historic town in western Russia, known as a former medieval center and namesake of the Principality of Trubchevsk.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a1a09881908d97270d6971a25a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e677e886a08190952b828fedd2a411 completed April 20, 2026, 7 p.m.
Created at: April 16, 2026, 11:22 a.m.