Triple

T18849704
Position Surface form Disambiguated ID Type / Status
Subject Sete Rios E461007 entity
Predicate hasConnectionTo P845 FINISHED
Object Lisbon Entrecampos 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: Lisbon Entrecampos | Statement: [Sete Rios, hasConnectionTo, Lisbon Entrecampos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisbon Entrecampos
Context triple: [Sete Rios, hasConnectionTo, Lisbon Entrecampos]
  • A. Lisboa Entrecampos chosen
    Lisboa Entrecampos is a major railway station in Lisbon, Portugal, serving suburban, regional, and long-distance trains and acting as an important transport hub in the city.
  • B. Vila Franca do Campo
    Vila Franca do Campo is a coastal town and municipality in the Azores archipelago of Portugal, known for its historic center and nearby islet popular for swimming and diving.
  • C. Odivelas
    Odivelas is a suburban city and municipality in the Lisbon metropolitan area of Portugal, known for its residential character and proximity to the capital.
  • D. Estoril
    Estoril is a coastal resort town in the municipality of Cascais, Portugal, known for its beaches, casino, and historic role as a refuge for exiled royalty and political figures.
  • E. Lisboa Sete Rios
    Lisboa Sete Rios is a major railway and bus interchange in Lisbon, Portugal, serving regional and suburban train lines as well as long-distance coach services.
  • 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_69d8dcfa11e4819090ab1ef5bdcd2b2e completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5b8f1abdc819081638ed384da191e completed April 20, 2026, 5:26 a.m.
Created at: April 10, 2026, 11:56 a.m.