Triple

T22779954
Position Surface form Disambiguated ID Type / Status
Subject Zona da Mata Paraibana E563807 entity
Predicate contains P35 FINISHED
Object Santa Rita NE NERFINISHED

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: Santa Rita | Statement: [Zona da Mata Paraibana, contains, Santa Rita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Rita
Context triple: [Zona da Mata Paraibana, contains, Santa Rita]
  • A. Santa Rita
    Santa Rita is a municipality in the province of Pampanga in the Philippines, known for its agricultural products and traditional local festivals.
  • B. Santa Rita
    Santa Rita is a residential district in the city of Turin, Italy, known for its urban character and proximity to major sports and public facilities.
  • C. Santa Rita
    Santa Rita is a municipality and town located in the Cortés Department of northwestern Honduras.
  • D. Santa Rita chosen
    Santa Rita is a municipality in the Brazilian state of Paraíba, known for its proximity to the state capital João Pessoa and its role in the region’s industrial and economic activities.
  • E. Santa Rita
    Santa Rita is a village in Guam known for its proximity to U.S. military installations and its location along the island’s western coast.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24554497c819080b996e071de27c2 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17b63d348819085668e3d9ac78ffa completed April 29, 2026, 3:30 a.m.
Created at: April 17, 2026, 3:28 p.m.