Triple

T9965159
Position Surface form Disambiguated ID Type / Status
Subject Alte E195664 entity
Predicate locatedNear P294 FINISHED
Object Serra do Caldeirão E733984 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: Serra do Caldeirão | Statement: [Alte, locatedNear, Serra do Caldeirão]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serra do Caldeirão
Context triple: [Alte, locatedNear, Serra do Caldeirão]
  • A. Serra do Caldeirão chosen
    Serra do Caldeirão is a mountain range in southern Portugal known for its rolling hills, cork oak forests, and traditional rural landscapes.
  • B. Serra da Barriga
    Serra da Barriga is a historic hill in Alagoas, Brazil, renowned as the main site of the Quilombo dos Palmares, one of the most important communities of escaped enslaved Africans in Brazilian history.
  • C. Serra do Alvão
    Serra do Alvão is a mountainous natural area in northern Portugal known for its rugged granite landscapes, waterfalls, and inclusion in the Alvão Natural Park.
  • D. Serra da Nave
    Serra da Nave is a mountainous area in northern Portugal that forms part of the natural landscape influencing the climate and viticulture of the Dão wine region.
  • E. Serra da Lousã
    Serra da Lousã is a mountain range in central Portugal known for its schist villages, dense forests, and popular hiking and nature tourism routes.
  • 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_69ca82ebd1288190912f9e4482d1fa35 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb71c38488190a6f3cda11994f6a2 completed April 2, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23da2d7988190b8603ddb151996d9 completed April 5, 2026, 10:46 a.m.
Created at: March 30, 2026, 8:47 p.m.