Triple

T2649139
Position Surface form Disambiguated ID Type / Status
Subject Rybinsk Reservoir E53854 entity
Predicate hasShorelineCity P969 FINISHED
Object Cherepovets E217616 NE FINISHED

How this triple was built (3 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: Cherepovets | Statement: [Rybinsk Reservoir, hasShorelineCity, Cherepovets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cherepovets
Context triple: [Rybinsk Reservoir, hasShorelineCity, Cherepovets]
  • A. Cherepovets chosen
    Cherepovets is a major industrial city in northwestern Russia, known especially for its large steel production and chemical industries.
  • B. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • C. Kirov
    Kirov is the revolutionary pseudonym of Sergei Kirov, a prominent early Soviet political leader and close associate of Joseph Stalin.
  • D. Elektrostal
    Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
  • E. Kaluga
    Kaluga is a historic city in western Russia known as a regional administrative center and an important site in several Russian uprisings and military campaigns.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasShorelineCity
Context triple: [Rybinsk Reservoir, hasShorelineCity, Cherepovets]
  • A. hasCityOnShore chosen
    Indicates that a city is located on or directly adjacent to the shore of a body of water.
  • B. hasShorelineCommunity
    Indicates that a place or region includes or is associated with a community located along its shoreline.
  • C. hasShorelineCountry
    Indicates that a country possesses a coastline or land boundary directly adjacent to a particular body of water or coastal region.
  • D. hasShorelineUse
    Indicates that a geographic area or property is used for a particular type of activity or purpose along its shoreline.
  • E. hasShoreOn
    Indicates that one geographic entity borders or is directly adjacent to the shore of another body of water.
  • F. None of above.

Provenance (4 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_69ab495e192081909c77b622e8e7e15a completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd91ca1288190ba302b04bac4c153 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69b503cf9f8881908dc371d5acb952cf completed March 14, 2026, 6:44 a.m.
PD Predicate disambiguation batch_69abd814298c8190952f05aed43f6bb8 completed March 7, 2026, 7:47 a.m.
Created at: March 6, 2026, 9:53 p.m.