Triple

T10699988
Position Surface form Disambiguated ID Type / Status
Subject Western Ohio E252247 entity
Predicate containsCity P294 FINISHED
Object Vandalia, Ohio E199256 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: Vandalia, Ohio | Statement: [Western Ohio, containsCity, Vandalia, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vandalia, Ohio
Context triple: [Western Ohio, containsCity, Vandalia, Ohio]
  • A. Vandalia, Ohio chosen
    Vandalia, Ohio is a suburban city in Montgomery County that serves as a key community in the Dayton metropolitan area of the Miami Valley region.
  • B. Havana, Ohio
    Havana, Ohio is a small unincorporated community located in Huron County in north-central Ohio.
  • C. 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.
  • D. Fairborn, Ohio
    Fairborn, Ohio is a city in Greene County that forms part of the Dayton metropolitan area in southwestern Ohio.
  • E. Tallmadge, Ohio
    Tallmadge, Ohio is a small city in northeastern Ohio known for its historic New England–style town center and early 19th-century origins.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd8abd7c81909c274aa1699a3695 completed April 9, 2026, 1:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69e623a9711081908eac4238a717305c completed April 20, 2026, 1:01 p.m.
Created at: April 8, 2026, 9:12 p.m.