Triple

T10769096
Position Surface form Disambiguated ID Type / Status
Subject Province of Lleida E254027 entity
Predicate containsRegion P285 FINISHED
Object Urgell E619842 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: Urgell | Statement: [Province of Lleida, containsRegion, Urgell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urgell
Context triple: [Province of Lleida, containsRegion, Urgell]
  • A. Urgell chosen
    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.
  • B. Besalú
    Besalú is a well-preserved medieval town in Catalonia, Spain, renowned for its Romanesque architecture and iconic 12th-century stone bridge.
  • 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. Tàrrega
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
  • 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_69f716adaed081909a6c026f9e232381 completed May 3, 2026, 9:34 a.m.
Created at: April 8, 2026, 9:16 p.m.