Triple

T23144756
Position Surface form Disambiguated ID Type / Status
Subject Medina County E577555 entity
Predicate hasCountySeat P383 FINISHED
Object Medina 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: Medina | Statement: [Medina County, hasCountySeat, Medina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medina
Context triple: [Medina County, hasCountySeat, Medina]
  • A. Medina chosen
    Medina is a small suburban city in Minnesota known for its rural character, parks, and proximity to the Minneapolis–Saint Paul metropolitan area.
  • B. Medina
    Medina is a common Spanish-origin surname found across the Spanish-speaking world and among their diasporas.
  • C. Medina
    Medina was a Spanish women's magazine associated with the Franco-era Sección Femenina that promoted traditional gender roles and nationalist ideology.
  • D. Medina
    Medina is a municipality in the Cundinamarca Department of Colombia, known for its rural landscapes and location within the Alto Guavio region.
  • E. Medina
    Medina is a coastal municipality in the Philippines known for its scenic shoreline along Macajalar Bay and its largely rural, agriculture-based communities.
  • 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_69e245f8e6248190ba3d58e068b4dccb completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18ecd40108190aaad7faf754b7936 completed April 29, 2026, 4:53 a.m.
Created at: April 17, 2026, 4:01 p.m.