Triple

T23227711
Position Surface form Disambiguated ID Type / Status
Subject Pamiers E581057 entity
Predicate hasTwinTown P919 FINISHED
Object Tàrrega 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: Tàrrega | Statement: [Pamiers, hasTwinTown, Tàrrega]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tàrrega
Context triple: [Pamiers, hasTwinTown, Tàrrega]
  • A. Tàrrega chosen
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
  • B. Besalú
    Besalú is a well-preserved medieval town in Catalonia, Spain, renowned for its Romanesque architecture and iconic 12th-century stone bridge.
  • C. Urgell
    Urgell is a historical comarca in inland Catalonia, known for its agricultural landscapes, medieval towns, and role as part of the broader Urgell region that includes the famous bishopric and valley.
  • D. Berga
    Berga is a historic town in Catalonia, Spain, known for its mountainous surroundings and the traditional Patum de Berga festival.
  • E. Berga
    Berga is a Swedish locality best known as a major naval base and training center for the Swedish Navy.
  • 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_69e246043c48819089bae72c9a9c306c completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f1922f5b4081908145d66ea7534493 completed April 29, 2026, 5:07 a.m.
Created at: April 17, 2026, 4:09 p.m.