Triple

T10769079
Position Surface form Disambiguated ID Type / Status
Subject Province of Lleida E254027 entity
Predicate contains P35 FINISHED
Object Tàrrega E427926 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: Tàrrega | Statement: [Province of Lleida, contains, Tàrrega]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tàrrega
Context triple: [Province of Lleida, contains, 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 (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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d7322f9968819098b0ad54b913bfe4 completed April 9, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a0e90e48190af6b802697d3256f completed May 3, 2026, 8:40 a.m.
Created at: April 8, 2026, 9:16 p.m.