Triple

T21287428
Position Surface form Disambiguated ID Type / Status
Subject Laguna de Apoyeque E524696 entity
Predicate nearbySettlement P350 FINISHED
Object Mateare 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: Mateare | Statement: [Laguna de Apoyeque, nearbySettlement, Mateare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mateare
Context triple: [Laguna de Apoyeque, nearbySettlement, Mateare]
  • A. Mateare chosen
    Mateare is a Nicaraguan town located near the capital Managua, known for its position along the shores of Lake Managua (Lago Xolotlán).
  • B. Mazzorbo
    Mazzorbo is a quiet island in the northern Venetian Lagoon known for its vineyards, colorful houses, and connection by bridge to the more famous island of Burano.
  • C. Moltrasio
    Moltrasio is a picturesque lakeside town on the western shore of Lake Como in northern Italy, known for its historic villas and scenic views.
  • D. Landana
    Landana is a coastal town in Angola’s Cabinda exclave, historically known as a regional trading and missionary center.
  • E. Marimonda
    Marimonda is a traditional, comical carnival character from Colombia, known for its exaggerated mask with a long nose and floppy ears, especially associated with the Barranquilla Carnival.
  • 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d7c57c8190bc4180ea590a62d4 completed April 21, 2026, 8:35 a.m.
Created at: April 16, 2026, 4:03 p.m.