Triple

T629382
Position Surface form Disambiguated ID Type / Status
Subject Madeira E15891 entity
Predicate hasCapital P204 FINISHED
Object Funchal E27897 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: Funchal | Statement: [Madeira, hasCapital, Funchal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Funchal
Context triple: [Madeira, hasCapital, Funchal]
  • A. Funchal, Madeira, Portugal chosen
    Funchal, Madeira, Portugal is the capital city of Portugal’s Madeira archipelago, known for its scenic harbor, subtropical climate, and as the hometown of footballer Cristiano Ronaldo.
  • B. Ponta Delgada
    Ponta Delgada is the largest city and main economic and administrative center of the Azores archipelago in Portugal, located on the island of São Miguel.
  • C. Vilamoura
    Vilamoura is a major Portuguese resort town in the Algarve, known for its large marina, golf courses, beaches, and upscale tourist facilities.
  • D. 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.
  • E. Tavira
    Tavira is a historic coastal town in Portugal’s Algarve region, known for its picturesque old town, Roman bridge, and nearby island beaches.
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e5b5a308190a62165f9275e2f5f completed March 1, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a56938be6481909a8eba01f5d856c1 completed March 2, 2026, 10:40 a.m.
Created at: March 1, 2026, 7:35 p.m.