Triple

T12312715
Position Surface form Disambiguated ID Type / Status
Subject São Vicente E293520 entity
Predicate hasIsland P970 FINISHED
Object Ilha de São Vicente E102933 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: Ilha de São Vicente | Statement: [São Vicente, hasIsland, Ilha de São Vicente]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ilha de São Vicente
Context triple: [São Vicente, hasIsland, Ilha de São Vicente]
  • A. São Vicente chosen
    São Vicente is a prominent island in Cape Verde known for its cultural hub Mindelo, vibrant music scene, and important Atlantic port.
  • B. São Vicente
    São Vicente is a coastal Brazilian city in the state of São Paulo, recognized as one of the country’s oldest European-founded settlements.
  • C. Ilha do Monteiro
    Ilha do Monteiro is an island district within the coastal Brazilian city of Recife, known for its urban setting amid the city’s network of rivers and estuaries.
  • D. Tarrafal de São Nicolau
    Tarrafal de São Nicolau is a coastal town and important population center on the island of São Nicolau in Cape Verde.
  • E. Ilhéus
    Ilhéus is a historic coastal city in northeastern Brazil known for its cacao production, beaches, and role as the setting of several novels by writer Jorge Amado.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f03d3c88190baedffb83465bff8 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a9d50b081908f0bdb7a2ca2832a completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:53 p.m.