Triple

T20028988
Position Surface form Disambiguated ID Type / Status
Subject Podolsk Urban Okrug E495068 entity
Predicate hasCapital P204 FINISHED
Object Podolsk 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: Podolsk | Statement: [Podolsk Urban Okrug, hasCapital, Podolsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Podolsk
Context triple: [Podolsk Urban Okrug, hasCapital, Podolsk]
  • A. Podolsk chosen
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • B. Priozersk
    Priozersk is a small town in northwestern Russia known for its historic fortress Korela and its location on the shores of Lake Ladoga.
  • C. Smolensk
    Smolensk is a historic city in western Russia near the Belarusian border, known for its strategic location and centuries-old fortifications.
  • D. Zvenigorod
    Zvenigorod is a historic town near Moscow, Russia, known for its ancient monasteries, traditional Russian architecture, and role as a cultural and spiritual center.
  • E. Elektrostal
    Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662908df081909a6c8ccf0dd90fff completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:36 p.m.