Triple

T13314189
Position Surface form Disambiguated ID Type / Status
Subject Ponent region E317147 entity
Predicate centeredAround P1939 FINISHED
Object city of Lleida E80563 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: city of Lleida | Statement: [Ponent region, centeredAround, city of Lleida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Lleida
Context triple: [Ponent region, centeredAround, city of Lleida]
  • A. Lleida chosen
    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.
  • B. 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.
  • C. Igualada
    Igualada is a historic town in Catalonia, Spain, known for its traditional textile and leather industries and its location near Barcelona.
  • D. Montmeló
    Montmeló is a municipality in Catalonia, Spain, best known for hosting the Circuit de Barcelona-Catalunya, a major venue for Formula 1 and MotoGP races.
  • E. Girona
    Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f8a86481909ea2942c63037b77 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716ec2ec08190a6e37795b422fe71 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:29 p.m.