Triple

T2025671
Position Surface form Disambiguated ID Type / Status
Subject Salvador Dalí E44401 entity
Predicate placeOfBirth P1 FINISHED
Object Figueres E42935 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: Figueres | Statement: [Salvador Dalí, placeOfBirth, Figueres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Figueres
Context triple: [Salvador Dalí, placeOfBirth, Figueres]
  • A. Figueres chosen
    Figueres is a town in Catalonia, Spain, best known as the birthplace of surrealist artist Salvador Dalí and home to the Dalí Theatre-Museum.
  • B. Girona
    Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
  • C. 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.
  • D. Ripoll
    Ripoll is a Spanish surname of Catalan origin, notably borne by Colombian singer Shakira.
  • E. Tarragona
    Tarragona is a historic port city in northeastern Spain, renowned for its well-preserved Roman ruins and status as a major cultural and economic center in Catalonia.
  • 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_69a889144f2481909932f0746a93023d completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb8f3faa08190a48ae1355d6e009f completed March 7, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6527c5a481909260377ae3b3fffd completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:38 p.m.