Triple

T14227994
Position Surface form Disambiguated ID Type / Status
Subject Kpong Dam E352672 entity
Predicate connectsWith P37 FINISHED
Object Akosombo Dam E370226 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: Akosombo Dam | Statement: [Kpong Dam, connectsWith, Akosombo Dam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akosombo Dam
Context triple: [Kpong Dam, connectsWith, Akosombo Dam]
  • A. Akosombo Dam chosen
    Akosombo Dam is a major hydroelectric dam in Ghana that created Lake Volta and supplies a significant portion of the country’s electricity.
  • B. Afobaka Dam
    Afobaka Dam is a major hydroelectric dam in Suriname that created the Brokopondo Reservoir and supplies much of the country’s electricity.
  • C. Roseires Dam
    Roseires Dam is a major hydroelectric and irrigation dam on the Blue Nile in Sudan, crucial for water storage, power generation, and flood control in the region.
  • D. Itumbiara Dam
    Itumbiara Dam is a large hydroelectric dam in Brazil known for generating significant electricity and forming one of the country’s major artificial reservoirs.
  • E. Inga II Dam
    Inga II Dam is a major hydroelectric power facility on the Congo River in the Democratic Republic of the Congo, forming part of the Inga Falls complex and supplying electricity to the region and beyond.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de622a48508190bbfedb762bd1674d completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c2bbfec81909ade3dd4306d69e3 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:07 a.m.