Triple

T10084045
Position Surface form Disambiguated ID Type / Status
Subject Carvoeiro Beach E215174 entity
Predicate locatedIn P40 FINISHED
Object Lagoa municipality E41623 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: Lagoa municipality | Statement: [Carvoeiro Beach, locatedIn, Lagoa municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lagoa municipality
Context triple: [Carvoeiro Beach, locatedIn, Lagoa municipality]
  • A. Municipality of Lagoa chosen
    The Municipality of Lagoa is a coastal local government area in Portugal’s Algarve region, known for its beaches, cliffs, and tourism-centered economy.
  • B. Satão Municipality
    Satão Municipality is a local administrative region in central Portugal known for its rural character and location within the Viseu District.
  • C. Maio Municipality
    Maio Municipality is a local government area encompassing the island of Maio in Cape Verde, responsible for its administrative and civic management.
  • D. Tenjo Municipality
    Tenjo Municipality is a town and municipality in the Cundinamarca Department of Colombia, located in the Bogotá savanna near the country's capital.
  • E. Mortágua Municipality
    Mortágua Municipality is a local administrative region in central Portugal known for its rural landscapes, forests, and small-town communities.
  • 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_69ca83a1eed081908b2e9580f2ebeea7 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd044c1ec8190b5b48cdb0584d00c completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b675f4b08190bd8285f210191b93 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.