Triple

T19418408
Position Surface form Disambiguated ID Type / Status
Subject Genrikh Yagoda E485779 entity
Predicate placeOfBirth P1 FINISHED
Object Rybinsk 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: Rybinsk | Statement: [Genrikh Yagoda, placeOfBirth, Rybinsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rybinsk
Context triple: [Genrikh Yagoda, placeOfBirth, Rybinsk]
  • A. Rybinsk chosen
    Rybinsk is a historic Russian city on the Volga River known for its role as a major river port and grain-shipping center.
  • B. Rybinsk Reservoir
    Rybinsk Reservoir is a large artificial lake in Russia, created by damming the Volga and several tributaries, and is one of the country’s largest and historically most significant reservoirs.
  • C. Tsimlyansk
    Tsimlyansk is a town in Rostov Oblast, Russia, known for its proximity to the Tsimlyansk Reservoir and its role in regional hydroelectric power and agriculture.
  • D. Tsimlyansk Reservoir
    Tsimlyansk Reservoir is a large artificial lake on the Don River in southwestern Russia, created for hydroelectric power, irrigation, and navigation.
  • E. Votkinsk Reservoir
    Votkinsk Reservoir is a large artificial lake in Russia formed by damming the Kama River, primarily used for hydroelectric power generation, navigation, and water regulation.
  • 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_69d8e8d688f881909c85104a62e09d8a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62afbaf0c8190913eda4b04efbe67 completed April 20, 2026, 1:32 p.m.
Created at: April 10, 2026, 1:37 p.m.