Triple

T10860917
Position Surface form Disambiguated ID Type / Status
Subject Kolomenskaya E256399 entity
Predicate hasRussianName P20560 FINISHED
Object Коломенская E256399 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: Коломенская | Statement: [Kolomenskaya, hasRussianName, Коломенская]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Коломенская
Context triple: [Kolomenskaya, hasRussianName, Коломенская]
  • A. Kolomenskaya chosen
    Kolomenskaya is a Moscow Metro station on the Zamoskvoretskaya Line, serving the Kolomenskoye area in the southern part of the city.
  • B. Sergiyev Posad
    Sergiyev Posad is a historic Russian town best known as a major center of Orthodox Christianity and home to the UNESCO-listed Trinity Lavra of St. Sergius monastery.
  • C. Krylatskoye
    Krylatskoye is a Moscow Metro station serving the Krylatskoye District in western Moscow, Russia.
  • D. Kolomna
    Kolomna is a historic Russian city southeast of Moscow, known for its well-preserved kremlin, medieval architecture, and traditional pastila confectionery.
  • E. Kitay-gorod
    Kitay-gorod is a historic central district of Moscow known for its medieval walls, important government and commercial buildings, and proximity to Red Square and the Kremlin.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7515186f08190a5cc388a7d936c4f completed April 9, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69e154c05bf081909d1892c6c81a5f2c completed April 16, 2026, 9:29 p.m.
Created at: April 8, 2026, 9:20 p.m.