Triple

T7614675
Position Surface form Disambiguated ID Type / Status
Subject Sal (Cape Verde) E172331 entity
Predicate hasSettlement P1068 FINISHED
Object Palmeira E420994 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: Palmeira | Statement: [Sal (Cape Verde), hasSettlement, Palmeira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palmeira
Context triple: [Sal (Cape Verde), hasSettlement, Palmeira]
  • A. Palmeira chosen
    Palmeira is a coastal town on the island of Sal in Cape Verde, known for its fishing harbor and role as a local transport and trade hub.
  • B. Palmeira dos Índios
    Palmeira dos Índios is a municipality in the Brazilian state of Alagoas, known for its cultural heritage and historical association with writer and politician Graciliano Ramos.
  • C. Cariri
    Cariri is a microregion in the state of Ceará, Brazil, known for its cultural heritage, religious tourism, and distinctive semi-arid landscapes.
  • D. Nipomo
    Nipomo is a small unincorporated community in California’s Central Coast region, known for its agricultural roots and proximity to the Pacific Ocean in southern San Luis Obispo County.
  • E. Itaquaquecetuba
    Itaquaquecetuba is a municipality in the Greater São Paulo metropolitan area of southeastern Brazil, known for its rapid urban growth and industrial activity.
  • 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_69c6994f50808190ba228764bb422417 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa4392e881908ed1ab3f64b41600 completed March 27, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8686d16808190bc431c43c0928f6e completed March 28, 2026, 11:46 p.m.
Created at: March 27, 2026, 3:55 p.m.