Triple

T20632680
Position Surface form Disambiguated ID Type / Status
Subject Moraine Airpark E506995 entity
Predicate owner P347 FINISHED
Object City of Moraine E445427 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: City of Moraine | Statement: [Moraine Airpark, owner, City of Moraine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Moraine
Context triple: [Moraine Airpark, owner, City of Moraine]
  • A. Moraine, Ohio chosen
    Moraine, Ohio is a small industrial city near Dayton known for its history of automobile manufacturing and assembly plants.
  • B. Urbancrest, Ohio
    Urbancrest, Ohio is a small village in central Ohio that functions as a residential suburb within the Columbus metropolitan area.
  • C. Wintersville, Ohio
    Wintersville, Ohio is a small village in eastern Ohio that serves as a residential community near Steubenville in Jefferson County.
  • D. Minerva, Ohio
    Minerva, Ohio is a small village in northeastern Ohio known for its historic downtown and location along the historic Lincoln Highway.
  • E. Woodmere, Ohio
    Woodmere, Ohio is a small suburban village in Cuyahoga County known for its upscale retail and commercial corridor along Chagrin Boulevard.
  • 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_69e0b4bd4a0081908d4e97a590a33fb2 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6ad0bdcd88190a59d68e03370b271 completed April 20, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08c585df208190becf0a78fad805f0 completed May 16, 2026, 7:29 p.m.
Created at: April 16, 2026, 11:42 a.m.