Triple

T23371964
Position Surface form Disambiguated ID Type / Status
Subject Матуа E593498 entity
Predicate имеетВулкан P6356 FINISHED
Object Сарычева NE NERFINISHED

How this triple was built (4 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: Сарычева | Statement: [Матуа, имеетВулкан, Сарычева]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Сарычева
Context triple: [Матуа, имеетВулкан, Сарычева]
  • A. Korcheva
    Korcheva was a historical town in the Tver region of Russia that served as an administrative center before being submerged by the Ivankovo Reservoir in the 1930s.
  • B. Vasilyeva
    Vasilyeva is a common Russian surname, typically the feminine form of Vasilyev, derived from the given name Vasily.
  • C. Skhodnenskaya
    Skhodnenskaya is a Moscow Metro station on the Tagansko-Krasnopresnenskaya Line serving the northwestern part of the city.
  • D. Tikhonova
    Tikhonova is a Russian surname most prominently associated with Katerina Tikhonova, a public figure widely reported to be one of Vladimir Putin’s daughters.
  • E. Tarasova
    Tarasova is a Russian surname most prominently associated with Tatiana Tarasova, a renowned figure skating coach and former competitor.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Сарычева
Target entity description: Сарычева — действующий стратовулкан на острове Матуа в центральной части Курильской гряды, известный своими частыми извержениями и конической формой.
  • A. Korcheva
    Korcheva was a historical town in the Tver region of Russia that served as an administrative center before being submerged by the Ivankovo Reservoir in the 1930s.
  • B. Vasilyeva
    Vasilyeva is a common Russian surname, typically the feminine form of Vasilyev, derived from the given name Vasily.
  • C. Skhodnenskaya
    Skhodnenskaya is a Moscow Metro station on the Tagansko-Krasnopresnenskaya Line serving the northwestern part of the city.
  • D. Tikhonova
    Tikhonova is a Russian surname most prominently associated with Katerina Tikhonova, a public figure widely reported to be one of Vladimir Putin’s daughters.
  • E. Tarasova
    Tarasova is a Russian surname most prominently associated with Tatiana Tarasova, a renowned figure skating coach and former competitor.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: имеетВулкан
Context triple: [Матуа, имеетВулкан, Сарычева]
  • A. hasVolcano chosen
    Indicates that one entity possesses, contains, or is the location of a volcano.
  • B. hasVolcanicVents
    Indicates that one entity possesses or contains volcanic vents associated with another entity or location.
  • C. isVolcanic
    Indicates that something is characterized by or related to volcanic activity, such as originating from, produced by, or associated with a volcano.
  • D. hasFumaroles
    Indicates the presence of fumaroles (openings emitting volcanic gases or steam) associated with an entity.
  • E. associatedVolcano
    Indicates that there is a specific volcano linked or connected to the referenced entity, such as by location, impact, or relevance.
  • F. None of above.

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_69e25d2593c88190bcdf4a716a94ccb2 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a3af45ec8190a32aa4e5f04f6756 completed April 29, 2026, 6:22 a.m.
PD Predicate disambiguation batch_69f061c7aaa48190a58ce93f87155ffc completed April 28, 2026, 7:29 a.m.
Created at: April 17, 2026, 5:32 p.m.