Triple

T6008445
Position Surface form Disambiguated ID Type / Status
Subject Mato Grosso do Sul E133771 entity
Predicate hasCity P316 FINISHED
Object Corumbá E137038 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: Corumbá | Statement: [Mato Grosso do Sul, hasCity, Corumbá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Corumbá
Context triple: [Mato Grosso do Sul, hasCity, Corumbá]
  • A. Corumbá chosen
    Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
  • B. Combarbalá
    Combarbalá is a small Chilean town and municipality in the Coquimbo Region, known for its semi-arid landscapes, goat farming, and distinctive combarbalite stone crafts.
  • C. Conceição
    Conceição is a civil parish located on Faial Island in the Azores archipelago of Portugal.
  • D. Itapira
    Itapira is a municipality in southeastern Brazil known for its agricultural activities and location within the interior of the state of São Paulo.
  • E. Ciluba
    Ciluba is a Bantu language spoken primarily in the Democratic Republic of the Congo, especially in the Kasai region.
  • 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_69c00872444c8190bfaf1739dcec765c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f154ca481909431baf4feecc16d completed March 22, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1089bd870819096c0f6c7cf484c50 completed March 23, 2026, 9:32 a.m.
Created at: March 22, 2026, 4:06 p.m.