Triple

T10645109
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan Area of Barcelona E250814 entity
Predicate containsMunicipality P852 FINISHED
Object Tordera E878556 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: Tordera | Statement: [Metropolitan Area of Barcelona, containsMunicipality, Tordera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tordera
Context triple: [Metropolitan Area of Barcelona, containsMunicipality, Tordera]
  • A. Tordera chosen
    Tordera is a municipality in the Maresme comarca of Catalonia, Spain, known for its rural landscapes and proximity to the Costa Brava.
  • B. Noguera Pallaresa
    Noguera Pallaresa is a river in the Catalan Pyrenees of northeastern Spain, renowned for its whitewater rafting and kayaking.
  • C. Santpedor
    Santpedor is a small town in Catalonia, Spain, best known internationally as the birthplace of football manager Pep Guardiola.
  • D. Gironella
    Gironella is a small municipality in Catalonia, Spain, known for its historic textile industry and location along the Llobregat River.
  • E. Corberó
    Corberó is a Spanish surname most notably associated with actress Úrsula Corberó, known internationally for her role in the series "Money Heist" (La Casa de Papel).
  • 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_69e2161018408190bcb64efba0974f8c completed April 17, 2026, 11:14 a.m.
Created at: April 8, 2026, 9:05 p.m.