Triple

T10645098
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan Area of Barcelona E250814 entity
Predicate containsMunicipality P852 FINISHED
Object Ripollet E878035 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: Ripollet | Statement: [Metropolitan Area of Barcelona, containsMunicipality, Ripollet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ripollet
Context triple: [Metropolitan Area of Barcelona, containsMunicipality, Ripollet]
  • A. Ripollet chosen
    Ripollet is a municipality in the comarca of Vallès Occidental in Catalonia, northeastern Spain, forming part of the Barcelona metropolitan area.
  • B. Cabrils
    Cabrils is a small municipality in the Maresme comarca of Catalonia, Spain, known for its residential character and proximity to the Mediterranean coast.
  • C. Cullera
    Cullera is a coastal town in eastern Spain known for its Mediterranean beaches, historic castle, and location at the mouth of the Júcar River.
  • D. Segorbe
    Segorbe is a historic town in eastern Spain known for its medieval architecture and traditional festivals, located in the Valencian Community.
  • E. Illescas
    Illescas is a historic town and municipality in central Spain, known for its traditional architecture and location between Madrid and Toledo.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfe120908190ab91c38d57133739 completed April 8, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c7b89a808190af9b2d4f37ad9012 completed April 18, 2026, 6:04 p.m.
Created at: April 8, 2026, 9:05 p.m.