Triple

T16979157
Position Surface form Disambiguated ID Type / Status
Subject Santa Ignacia E411894 entity
Predicate borderedBy P224 FINISHED
Object Gerona 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: Gerona | Statement: [Santa Ignacia, borderedBy, Gerona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gerona
Context triple: [Santa Ignacia, borderedBy, Gerona]
  • A. Girona chosen
    Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
  • B. Igualada
    Igualada is a historic town in Catalonia, Spain, known for its traditional textile and leather industries and its location near Barcelona.
  • C. Martorell
    Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
  • D. Lleida
    Lleida is a historic city in western Catalonia, Spain, known for its medieval Seu Vella cathedral and role as a regional agricultural and commercial center.
  • E. Montmeló
    Montmeló is a municipality in Catalonia, Spain, best known for hosting the Circuit de Barcelona-Catalunya, a major venue for Formula 1 and MotoGP races.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d185a9408190a991bf8a1ef694f0 completed April 18, 2026, 6:46 p.m.
Created at: April 10, 2026, 5:32 a.m.