Triple

T22656903
Position Surface form Disambiguated ID Type / Status
Subject Lady of Balaguer E559250 entity
Predicate territorialDesignation P14731 FINISHED
Object Balaguer, Lleida 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: Balaguer, Lleida | Statement: [Lady of Balaguer, territorialDesignation, Balaguer, Lleida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Balaguer, Lleida
Context triple: [Lady of Balaguer, territorialDesignation, Balaguer, Lleida]
  • A. Balaguer, Lleida, Catalonia, Spain chosen
    Balaguer is a historic town in the province of Lleida, Catalonia, Spain, known for its medieval architecture and location along the Segre River.
  • B. Pedralba
    Pedralba is a municipality in the province of Valencia, Spain, known for its rural landscape and location along the Turia 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. Garriga
    Garriga is a Spanish surname most notably borne by Ignacio Garriga, a contemporary Spanish politician.
  • E. Banyoles
    Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
  • 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_69e245489dd88190b1f674acf61c8769 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1765c62bc8190b3fcde76d6b6dfb6 completed April 29, 2026, 3:09 a.m.
Created at: April 17, 2026, 3:06 p.m.