Triple

T14227318
Position Surface form Disambiguated ID Type / Status
Subject ZESCO E352655 entity
Predicate serviceArea P82 FINISHED
Object Zambia E18189 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: Zambia | Statement: [ZESCO, serviceArea, Zambia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zambia
Context triple: [ZESCO, serviceArea, Zambia]
  • A. Zambia chosen
    Zambia is a landlocked country in south-central Africa known for the Victoria Falls on the Zambezi River, diverse wildlife, and copper-rich economy.
  • B. Zambia and Zimbabwe
    Zambia and Zimbabwe are neighboring landlocked countries in southern Africa that share the famous Victoria Falls along their common border.
  • C. Zimbabwe
    Zimbabwe is a landlocked country in southern Africa known for its dramatic landscapes, diverse wildlife, and historical sites such as Victoria Falls and the Great Zimbabwe ruins.
  • D. Malawi
    Malawi is a landlocked country in southeastern Africa known for Lake Malawi, its predominantly agricultural economy, and membership in regional and international organizations including the Commonwealth.
  • E. Tanzania and Zambia
    Tanzania and Zambia are neighboring countries in East and Southern Africa that share a long land and lake border, including part of the shoreline of Lake Tanganyika.
  • 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_69fd2802ba608190849313ff2661cd07 completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:07 a.m.