Triple

T9024641
Position Surface form Disambiguated ID Type / Status
Subject Frank Howard E216013 entity
Predicate placeOfDeath P21 FINISHED
Object Virginia, United States E5410 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: Virginia, United States | Statement: [Frank Howard, placeOfDeath, Virginia, United States]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Virginia, United States
Context triple: [Frank Howard, placeOfDeath, Virginia, United States]
  • A. Virginia chosen
    Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American history, including being home to several early presidents and key Revolutionary and Civil War sites.
  • B. Virginia
    Virginia is a small community located within the town of Georgina in Ontario, Canada.
  • C. Virginia
    Virginia is a coastal township in Montserrado County, Liberia, known for its beaches and proximity to the capital, Monrovia.
  • D. Washington, Virginia
    Washington, Virginia is a small historic town in the foothills of the Blue Ridge Mountains known for its preserved 18th-century character and acclaimed dining, including The Inn at Little Washington.
  • E. La Virginia
    La Virginia is a municipality in western Colombia known for its location along the Cauca River and its role as a commercial and transport hub in the Risaralda Department.
  • 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_69ca83a5fa88819088144801b4dd7245 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6a7b902c81909fcbdc433a1acf7a completed April 1, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffda9697c81908a1a9e447519ce05 completed April 3, 2026, 5:49 p.m.
Created at: March 30, 2026, 7:07 p.m.