Triple

T11453313
Position Surface form Disambiguated ID Type / Status
Subject Eastern Ohio E271457 entity
Predicate contains P35 FINISHED
Object Youngstown E26250 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: Youngstown | Statement: [Eastern Ohio, contains, Youngstown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Youngstown
Context triple: [Eastern Ohio, contains, Youngstown]
  • A. Youngstown chosen
    Youngstown is an industrial city in northeastern Ohio historically known for its steel production and central role in the Rust Belt’s economic rise and decline.
  • B. Youngstown, Pennsylvania
    Youngstown, Pennsylvania is a small unincorporated community and census-designated place in Westmoreland County, known for its location within the scenic Ligonier Valley region of southwestern Pennsylvania.
  • C. Lorain
    Lorain is an industrial city on Lake Erie in northern Ohio, historically known for its steel production and shipbuilding.
  • D. Akron
    Akron is an industrial city in northeastern Ohio known historically for its rubber and tire manufacturing industry.
  • E. Dresden, Ohio
    Dresden, Ohio is a small village in Muskingum County known historically as the original home of the Longaberger Company and its handcrafted baskets.
  • 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_69d6aadff8888190a13f253f0d460874 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d81c7057688190ad8aa99426e4ca30 completed April 9, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6040733648190a10f9553b3ac87a7 completed April 20, 2026, 10:46 a.m.
Created at: April 8, 2026, 9:35 p.m.