Triple

T20224795
Position Surface form Disambiguated ID Type / Status
Subject Mid-Ohio Valley Regional Airport E495349 entity
Predicate serves P98 FINISHED
Object Vienna, West Virginia 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: Vienna, West Virginia | Statement: [Mid-Ohio Valley Regional Airport, serves, Vienna, West Virginia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vienna, West Virginia
Context triple: [Mid-Ohio Valley Regional Airport, serves, Vienna, West Virginia]
  • A. Vienna, West Virginia chosen
    Vienna, West Virginia is a small city in northwestern West Virginia situated along the Ohio River, forming part of the Parkersburg metropolitan area.
  • B. Fairview, West Virginia
    Fairview, West Virginia is a small town in Marion County best known as the birthplace of legendary early 20th-century college football coach Fielding H. Yost.
  • C. Williamstown, West Virginia
    Williamstown, West Virginia, is a small city in the Mid-Ohio Valley region known for its location along the Ohio River and proximity to Parkersburg.
  • D. Athens, West Virginia
    Athens, West Virginia is a small town in southern West Virginia best known as the home of Concord University.
  • E. Madison, West Virginia
    Madison, West Virginia is a small town in the southern part of the state that serves as an administrative and commercial hub for the surrounding coal-mining region.
  • 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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66fd8f1948190adbb947a7870bb43 completed April 20, 2026, 6:26 p.m.
Created at: April 11, 2026, 11:39 p.m.