Triple

T2111785
Position Surface form Disambiguated ID Type / Status
Subject Crescent E42519 entity
Predicate servesCity P82 FINISHED
Object Charlottesville E78420 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: Charlottesville | Statement: [Crescent, servesCity, Charlottesville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charlottesville
Context triple: [Crescent, servesCity, Charlottesville]
  • A. Charlottesville, Virginia chosen
    Charlottesville, Virginia is an independent city in central Virginia best known as the home of the University of Virginia and the historic estate of Monticello.
  • B. Richmond
    Richmond is an industrial and residential city in California’s East Bay region, known for its waterfront along San Francisco Bay and its diverse, working-class communities.
  • C. Richmond
    Richmond is a town in southwest London, England, known for its historic riverside, expansive parkland, and affluent residential character.
  • D. Richmond
    Richmond is a coastal city in Metro Vancouver, British Columbia, known for its large Asian community, busy international airport, and extensive dike-protected waterfront.
  • E. Richmond
    Richmond is a masculine given name of English origin that has been borne by various notable figures, including military leaders and public officials.
  • 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_69a8871040f08190aac2e2d0ab6b47ad completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb0369a88190af02f0e4e05e2511 completed March 7, 2026, 5:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae95efea5c8190a8a63e36cf3247e7 completed March 9, 2026, 9:42 a.m.
Created at: March 4, 2026, 7:43 p.m.