Triple

T21664468
Position Surface form Disambiguated ID Type / Status
Subject A22 motorway (Portugal) E534674 entity
Predicate passesNear P416 FINISHED
Object Faro 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: Faro | Statement: [A22 motorway (Portugal), passesNear, Faro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faro
Context triple: [A22 motorway (Portugal), passesNear, Faro]
  • A. Faro chosen
    Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
  • B. Faro
    Faro is a small municipality in the Brazilian state of Pará, located within the Lower Amazon region and known for its riverside Amazonian environment and traditional communities.
  • C. Hvalvík
    Hvalvík is a small coastal village in the Faroe Islands known for its traditional wooden church and scenic fjord-side setting.
  • D. Klaksvík
    Klaksvík is the second-largest town in the Faroe Islands, known as an important fishing and commercial center located on the island of Borðoy.
  • E. Æðuvík
    Æðuvík is a small coastal village on the Faroe Islands’ island of Eysturoy, known for its scenic seaside setting and traditional Faroese character.
  • 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_69e0c467e1f48190af2650b19175abc4 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef6c0a2a58819086db5b5c1c0f3371 completed April 27, 2026, 2 p.m.
Created at: April 16, 2026, 6:36 p.m.