Triple

T13891649
Position Surface form Disambiguated ID Type / Status
Subject Intercidades E333984 entity
Predicate mainTerminus P388 FINISHED
Object Porto Campanhã E1019262 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: Porto Campanhã | Statement: [Intercidades, mainTerminus, Porto Campanhã]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porto Campanhã
Context triple: [Intercidades, mainTerminus, Porto Campanhã]
  • A. Porto-Campanhã chosen
    Porto-Campanhã is the main railway station in Porto, Portugal, serving as a central hub for long-distance and regional train services across the country.
  • B. Porto de Mós
    Porto de Mós is a Portuguese town and municipality known for its hilltop castle and location near the limestone landscapes and caves of central Portugal.
  • C. Figueira da Foz
    Figueira da Foz is a coastal Portuguese city at the mouth of the Mondego River, known for its wide sandy beaches and seaside tourism.
  • D. Figueira da Horta
    Figueira da Horta is a small village located on the island of Maio in Cape Verde.
  • E. Portimão
    Portimão is a coastal city and popular tourist destination in southern Portugal, known for its beaches, marina, and vibrant waterfront along the Arade River.
  • 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_69d81c5dd2d48190b7a5fc1e009de936 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de23a537d4819093c2bae2a244816a completed April 14, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea59d27bc81908ace0b7db9f57215 completed May 9, 2026, 3:10 a.m.
Created at: April 9, 2026, 10:15 p.m.