Triple

T10052747
Position Surface form Disambiguated ID Type / Status
Subject Bordeira E208785 entity
Predicate contains P35 FINISHED
Object Carrapateira E773758 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: Carrapateira | Statement: [Bordeira, contains, Carrapateira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carrapateira
Context triple: [Bordeira, contains, Carrapateira]
  • A. Carrapateira chosen
    Carrapateira is a small coastal village in Portugal’s Algarve region, known for its rugged cliffs, surfing beaches, and unspoiled natural scenery.
  • B. Carapebus
    Carapebus is a small coastal municipality in the state of Rio de Janeiro, Brazil, known for its lagoons, beaches, and ecological tourism.
  • C. Poilão
    Poilão is a small, uninhabited island in Guinea-Bissau’s Bijagós Archipelago, renowned as one of the world’s most important nesting sites for green sea turtles.
  • D. Guabiraba
    Guabiraba is a neighborhood and administrative district located in the northern part of Recife, in the state of Pernambuco, Brazil.
  • E. Gavião
    Gavião is a small rural municipality in eastern Portugal known for its scenic landscapes along the Tagus River and traditional Alentejo culture.
  • 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_69ca836094408190a36a1ea7e9a86fcd completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf9241208190b38e5e7a1604589c completed April 2, 2026, 2:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a4064a48190b4fdb6bf3ea5af05 completed April 5, 2026, 5:22 p.m.
Created at: March 30, 2026, 8:56 p.m.