Triple

T19185261
Position Surface form Disambiguated ID Type / Status
Subject James City County, Virginia E469685 entity
Predicate hasCountySeat P383 FINISHED
Object Williamsburg, 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: Williamsburg, Virginia | Statement: [James City County, Virginia, hasCountySeat, Williamsburg, Virginia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Williamsburg, Virginia
Context triple: [James City County, Virginia, hasCountySeat, Williamsburg, Virginia]
  • A. Williamsburg chosen
    Williamsburg is a historic colonial city in Virginia renowned for its well-preserved 18th-century architecture and living-history museum, Colonial Williamsburg.
  • B. Williamsburg
    Williamsburg is a small town located in Fremont County, Colorado, known for its rural character and proximity to the Rocky Mountains.
  • C. Williamsburg
    Williamsburg is a small village in Sierra County, New Mexico, located near the Rio Grande and close to the city of Truth or Consequences.
  • D. Williamsburg
    Williamsburg is a trendy Brooklyn neighborhood known for its vibrant arts scene, nightlife, and waterfront views of Manhattan.
  • E. Williamsburg
    Williamsburg is a small rural community located within Dundas County in eastern Ontario, Canada.
  • 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_69d8dd0ad9088190a173b32657ae2e7a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f6202b3881908b34ec4921fb90ca completed April 20, 2026, 9:47 a.m.
Created at: April 10, 2026, 12:07 p.m.