Triple

T6511929
Position Surface form Disambiguated ID Type / Status
Subject Millau E150156 entity
Predicate twinTown P1072 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: [Millau, twinTown, Figueres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Figueres
Context triple: [Millau, twinTown, 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. Tàrrega
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
  • D. Esplugues de Llobregat
    Esplugues de Llobregat is a municipality in the metropolitan area of Barcelona, Catalonia, known for its residential character and proximity to the Catalan capital.
  • E. 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.
  • 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_69c687ef291081909d437f035eef1cda completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c69f3c5eb88190a56723acd8096dd8 completed March 27, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb6421748190b8f2b77c77b153bc completed March 27, 2026, 6:24 p.m.
Created at: March 27, 2026, 1:44 p.m.