Triple

T10169823
Position Surface form Disambiguated ID Type / Status
Subject Voronezh Oblast E235300 entity
Predicate containsCity P294 FINISHED
Object Rossosh E744351 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: Rossosh | Statement: [Voronezh Oblast, containsCity, Rossosh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rossosh
Context triple: [Voronezh Oblast, containsCity, Rossosh]
  • A. Rossosh chosen
    Rossosh is a town in Voronezh Oblast, Russia, known as a regional center in the country’s southwest.
  • B. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • C. Odoyev
    Odoyev is a historic town in Tula Oblast, Russia, known as an old regional center with roots dating back to medieval Rus.
  • D. Oreshek
    Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
  • E. Rossau
    Rossau is a municipality in the German state of Saxony, located within the rural district of Mittelsachsen.
  • 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec9ba56481908b5265aea8ea8cbe completed April 2, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d300f7aafc8190be874efc755bd188 completed April 6, 2026, 12:40 a.m.
Created at: March 30, 2026, 9:10 p.m.