Triple

T10769076
Position Surface form Disambiguated ID Type / Status
Subject Province of Lleida E254027 entity
Predicate contains P35 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: [Province of Lleida, contains, City of Lleida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Lleida
Context triple: [Province of Lleida, contains, 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. Molins de Rei
    Molins de Rei is a municipality in the Barcelona metropolitan area of Catalonia, Spain, situated along the Llobregat River.
  • C. Igualada
    Igualada is a historic town in Catalonia, Spain, known for its traditional textile and leather industries and its location near Barcelona.
  • D. Martorell
    Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
  • E. 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.
  • 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_69f6fef311c4819094b6b08a62d3afb3 completed May 3, 2026, 7:53 a.m.
Created at: April 8, 2026, 9:16 p.m.