Triple

T1852321
Position Surface form Disambiguated ID Type / Status
Subject Vilamoura E41622 entity
Predicate locatedIn P40 FINISHED
Object Algarve E6079 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: Algarve | Statement: [Vilamoura, locatedIn, Algarve]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algarve
Context triple: [Vilamoura, locatedIn, Algarve]
  • A. Algarve chosen
    Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
  • B. southern Portugal
    Southern Portugal is the warm, largely rural and coastal region of Portugal that includes the Algarve and Alentejo, known for its beaches, historic towns, and Mediterranean climate.
  • C. Alentejo
    Alentejo is a large, sparsely populated region in southern Portugal known for its rolling plains, cork oak forests, vineyards, and historic whitewashed towns.
  • D. mainland Portugal
    Mainland Portugal is the continental part of the Portuguese Republic in southwestern Europe, comprising the country’s primary territory on the Iberian Peninsula.
  • E. northeastern Portugal
    Northeastern Portugal is a culturally distinct, sparsely populated region bordering Spain, known for its Mirandese-speaking communities, traditional rural landscapes, and historic towns.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb06999f4819086386aafb789a368 completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa037c1d4819088d057bb2f0ee2bd completed March 10, 2026, 4:38 a.m.
Created at: March 4, 2026, 7:33 p.m.