Triple

T10769103
Position Surface form Disambiguated ID Type / Status
Subject Province of Lleida E254027 entity
Predicate containsRegion P285 FINISHED
Object Pla d'Urgell E614163 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: Pla d'Urgell | Statement: [Province of Lleida, containsRegion, Pla d'Urgell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pla d'Urgell
Context triple: [Province of Lleida, containsRegion, Pla d'Urgell]
  • A. Pla d'Urgell chosen
    Pla d'Urgell is a comarca (county) in the inland plains of Catalonia, Spain, known for its irrigated agriculture and small rural towns.
  • B. Pedralbes
    Pedralbes is an affluent residential neighborhood in Barcelona known for its upscale homes, green spaces, and prestigious educational institutions.
  • C. Banyoles
    Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
  • D. Alt Urgell
    Alt Urgell is a mountainous comarca in the Catalan Pyrenees known for its natural landscapes, rural villages, and the town of La Seu d'Urgell.
  • E. Sant Celoni
    Sant Celoni is a town in Catalonia, Spain, located northeast of Barcelona in the Vallès Oriental comarca, known as a local commercial and transport hub between the Montseny and Montnegre natural areas.
  • 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_69e55621a88c8190b9611bf9e3b307de completed April 19, 2026, 10:24 p.m.
Created at: April 8, 2026, 9:16 p.m.