Triple

T14070496
Position Surface form Disambiguated ID Type / Status
Subject Lisbon–Porto main line E338592 entity
Predicate usedByService P1294 FINISHED
Object Intercidades E302851 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: Intercidades | Statement: [Lisbon–Porto main line, usedByService, Intercidades]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Intercidades
Context triple: [Lisbon–Porto main line, usedByService, Intercidades]
  • A. Intercidades chosen
    Intercidades is Portugal’s main long-distance intercity train service operated by the national railway company, connecting major cities across the country.
  • B. Rio de Janeiro–Belo Horizonte corridor
    The Rio de Janeiro–Belo Horizonte corridor is a major Brazilian transport and economic axis linking the cities of Rio de Janeiro and Belo Horizonte through a network of highways and railways.
  • C. Entre-os-Rios
    Entre-os-Rios is a Portuguese riverside parish known for its scenic location at the confluence of the Tâmega and Douro rivers.
  • D. Interlagos
    Interlagos is a famous motor racing circuit in São Paulo, Brazil, best known for hosting the Formula One Brazilian Grand Prix.
  • E. SuperVia
    SuperVia is the main commuter rail operator serving the metropolitan region of Rio de Janeiro, Brazil.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de568d0404819087e0fe37c72162cb completed April 14, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb66cfe2c8190af8354316d4f4df9 completed May 7, 2026, 3:57 p.m.
Created at: April 9, 2026, 10:21 p.m.