Triple

T18070055
Position Surface form Disambiguated ID Type / Status
Subject Ferreira do Zêzere E432400 entity
Predicate hasAttraction P105 FINISHED
Object Zêzere River 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: Zêzere River | Statement: [Ferreira do Zêzere, hasAttraction, Zêzere River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zêzere River
Context triple: [Ferreira do Zêzere, hasAttraction, Zêzere River]
  • A. Zêzere River chosen
    The Zêzere River is a major river in central Portugal known for its scenic valleys, hydroelectric dams, and role in feeding the Castelo de Bode Reservoir.
  • B. Tâmega River
    The Tâmega River is a significant river in the Iberian Peninsula that flows through northern Portugal and parts of Spain, contributing notably to the Douro River basin.
  • C. Rio Dão
    Rio Dão is the Portuguese name for the Dão River, a watercourse in central Portugal known for flowing through the Dão wine region.
  • D. Alto Tâmega
    Alto Tâmega is an inland subregion of northern Portugal known for its mountainous landscapes, thermal springs, and traditional rural communities.
  • E. Ribeira do Ulla
    Ribeira do Ulla is a subzone of Spain’s Rías Baixas wine region, known for producing fresh, aromatic white wines, particularly from the Albariño grape.
  • 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4cced29fc81908e87b4f1990fa0d8 completed April 19, 2026, 12:39 p.m.
Created at: April 10, 2026, 10:26 a.m.