Triple

T6837684
Position Surface form Disambiguated ID Type / Status
Subject Azores Airlines E157489 entity
Predicate serves P98 FINISHED
Object Madeira E15891 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: Madeira | Statement: [Azores Airlines, serves, Madeira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madeira
Context triple: [Azores Airlines, serves, Madeira]
  • A. Madeira chosen
    Madeira is a Portuguese archipelago in the North Atlantic Ocean known for its rugged volcanic landscapes, mild subtropical climate, and namesake fortified wine.
  • B. Azores
    The Azores are a remote Portuguese archipelago in the North Atlantic Ocean, known for their volcanic landscapes, lush greenery, and mild maritime climate.
  • C. Ilha de Faro
    Ilha de Faro is a coastal barrier island in southern Portugal known for its sandy beaches, lagoon landscapes, and role as a popular seaside destination near the city of Faro.
  • D. Tavira Island
    Tavira Island is a scenic barrier island off the Algarve coast of southern Portugal, known for its long sandy beaches, dunes, and protected natural habitats.
  • E. Santa Maria Island
    Santa Maria Island is the southernmost island of Portugal’s Azores archipelago, known for its warmer, drier climate and distinctive white-sand 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_69c6882c53608190b99aebef079b23bd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d67db4008190b86b497bf6f0c73a completed March 27, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b8a72af081909e5e6da123a47694 completed March 28, 2026, 11:16 a.m.
Created at: March 27, 2026, 2:19 p.m.