Triple

T2820900
Position Surface form Disambiguated ID Type / Status
Subject Loulé coastline E54805 entity
Predicate hasResortArea P10436 FINISHED
Object Vilamoura E41622 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: Vilamoura | Statement: [Loulé coastline, hasResortArea, Vilamoura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vilamoura
Context triple: [Loulé coastline, hasResortArea, Vilamoura]
  • A. Vilamoura chosen
    Vilamoura is a major Portuguese resort town in the Algarve, known for its large marina, golf courses, beaches, and upscale tourist facilities.
  • B. Albufeira
    Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
  • C. Praia da Luz
    Praia da Luz is a popular seaside resort village in Portugal’s Algarve region, known for its sandy beach, cliffs, and tourist-oriented waterfront.
  • 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. 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.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde6e85008190a08eb2bf8e393e7e completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0312dd4848190b30f6fcc11c2c954 completed March 10, 2026, 2:56 p.m.
Created at: March 6, 2026, 9:59 p.m.