Triple

T16092962
Position Surface form Disambiguated ID Type / Status
Subject Morro E390403 entity
Predicate partOf P40 FINISHED
Object Maio Municipality E390410 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: Maio Municipality | Statement: [Morro, partOf, Maio Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maio Municipality
Context triple: [Morro, partOf, Maio Municipality]
  • A. Maio Municipality chosen
    Maio Municipality is a local government area encompassing the island of Maio in Cape Verde, responsible for its administrative and civic management.
  • B. Satão Municipality
    Satão Municipality is a local administrative region in central Portugal known for its rural character and location within the Viseu District.
  • C. Mação Municipality
    Mação Municipality is a local administrative region in central Portugal known for its rural landscapes, historical villages, and archaeological heritage.
  • D. Fundão Municipality
    Fundão Municipality is a local administrative region in central Portugal known for its agricultural production, especially cherries, and its historic villages.
  • E. Tenjo Municipality
    Tenjo Municipality is a town and municipality in the Cundinamarca Department of Colombia, located in the Bogotá savanna near the country's capital.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1858ed09881909bde122971d95753 completed April 17, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff79a96d08190af69cbb18037f66e completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 4:59 a.m.