Triple

T1746870
Position Surface form Disambiguated ID Type / Status
Subject Municipality of Loulé E38353 entity
Predicate knownFor P22 FINISHED
Object Vilamoura resort 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 resort | Statement: [Municipality of Loulé, knownFor, Vilamoura resort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vilamoura resort
Context triple: [Municipality of Loulé, knownFor, Vilamoura resort]
  • 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. 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.
  • C. Quarteira resort
    Quarteira resort is a popular coastal holiday destination in Portugal’s Algarve region, known for its long sandy beaches, seaside promenade, and vibrant tourist infrastructure.
  • D. Costa da Caparica
    Costa da Caparica is a coastal town and popular beach destination just south of Lisbon, Portugal, known for its long sandy shoreline and Atlantic surf.
  • E. Albufeira
    Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63eabdf48190878ecde3d1b1faf3 completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69adb5c28ac881909ba2a7e5c2067127 completed March 8, 2026, 5:45 p.m.
Created at: March 4, 2026, 7:31 p.m.