Triple

T17002242
Position Surface form Disambiguated ID Type / Status
Subject Josep Puig i Cadafalch E412475 entity
Predicate placeOfBirth P1 FINISHED
Object Mataró 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: Mataró | Statement: [Josep Puig i Cadafalch, placeOfBirth, Mataró]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mataró
Context triple: [Josep Puig i Cadafalch, placeOfBirth, Mataró]
  • A. Mataró chosen
    Mataró is a coastal city in northeastern Spain known as an important commercial and industrial center on the Mediterranean near Barcelona.
  • B. Sabadell
    Sabadell is a major industrial and commercial city in Catalonia, Spain, known historically for its textile industry and now as part of the Barcelona metropolitan area.
  • C. Esplugues de Llobregat
    Esplugues de Llobregat is a municipality in the metropolitan area of Barcelona, Catalonia, known for its residential character and proximity to the Catalan capital.
  • D. Montmeló
    Montmeló is a municipality in Catalonia, Spain, best known for hosting the Circuit de Barcelona-Catalunya, a major venue for Formula 1 and MotoGP races.
  • E. Lleida
    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.
  • 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_69d886cb581c8190ab05f4b429c9cd85 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d37ec2b48190b4f997899d887ba8 completed April 18, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:32 a.m.