Triple

T1268875
Position Surface form Disambiguated ID Type / Status
Subject Lagos (Portugal) E15664 entity
Predicate locatedOn P40 FINISHED
Object Algarve coast 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 coast | Statement: [Lagos (Portugal), locatedOn, Algarve coast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algarve coast
Context triple: [Lagos (Portugal), locatedOn, Algarve coast]
  • A. Algarve chosen
    Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
  • B. 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.
  • 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. Covas do Douro
    Covas do Douro is a civil parish in northern Portugal’s Douro Valley, known for its wine-producing landscape and inclusion in the municipality of Sabrosa.
  • 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_69a4935a94308190bb92555b79032824 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4c03aaa8c8190bacb7de5a38329da completed March 1, 2026, 10:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbae1e55c8190a487084e16804e4d completed March 7, 2026, 11:55 p.m.
Created at: March 1, 2026, 7:50 p.m.