Triple

T14220207
Position Surface form Disambiguated ID Type / Status
Subject Sabor River E352468 entity
Predicate hasDam P8736 FINISHED
Object Baixo Sabor Dam E792448 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: Baixo Sabor Dam | Statement: [Sabor River, hasDam, Baixo Sabor Dam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baixo Sabor Dam
Context triple: [Sabor River, hasDam, Baixo Sabor Dam]
  • A. Guavio Dam
    Guavio Dam is a major hydroelectric dam in Colombia known for its large reservoir and significant contribution to the country’s power generation.
  • B. Barra Bonita Dam
    Barra Bonita Dam is a hydroelectric and navigation dam complex in the state of São Paulo, Brazil, known for regulating the Tietê River and forming the Barra Bonita Reservoir.
  • C. Jirau Dam
    Jirau Dam is a large hydroelectric power plant in Brazil, built on the Madeira River as part of the country’s major Amazon basin energy infrastructure.
  • D. Gouvães Dam chosen
    Gouvães Dam is a hydroelectric dam in northern Portugal that forms part of the Tâmega River energy complex, contributing to regional power generation and water management.
  • E. Baipaza Dam
    Baipaza Dam is a major hydroelectric dam in Tajikistan that harnesses the Vakhsh River to generate power and support regional water management.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6213801c8190a47705cd890b9ae7 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd55008a5c8190b005a12df7ef2f75 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:06 a.m.