Triple

T9393845
Position Surface form Disambiguated ID Type / Status
Subject Steven Pushkov E226092 entity
Predicate placeOfResidence P75 FINISHED
Object Clairton, Pennsylvania E158598 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: Clairton, Pennsylvania | Statement: [Steven Pushkov, placeOfResidence, Clairton, Pennsylvania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clairton, Pennsylvania
Context triple: [Steven Pushkov, placeOfResidence, Clairton, Pennsylvania]
  • A. Clairton, Pennsylvania chosen
    Clairton, Pennsylvania is a small industrial city in the Pittsburgh metropolitan area, historically known for its large coke production plant along the Monongahela River.
  • B. Chartiers, Pennsylvania
    Chartiers, Pennsylvania is a community in the Pittsburgh area best known as the birthplace of Baseball Hall of Famer Honus Wagner.
  • C. Bessemer, Pennsylvania
    Bessemer, Pennsylvania is a small borough in western Pennsylvania known historically for its steel and industrial heritage.
  • D. Mahoningtown
    Mahoningtown is a neighborhood and former independent community now incorporated into the city of New Castle in western Pennsylvania.
  • E. Aliquippa
    Aliquippa is a small industrial city in western Pennsylvania known historically for its steel production and location along the Ohio River.
  • 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_69ca842f7e3481908bf5bcf52e032dbd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd511150008190be04142e477e8bf1 completed April 1, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107949fe4819089f68a2c368af82f completed April 4, 2026, 12:44 p.m.
Created at: March 30, 2026, 7:45 p.m.