Triple

T841621
Position Surface form Disambiguated ID Type / Status
Subject Zambia E18189 entity
Predicate borderedBy P224 FINISHED
Object Mozambique E13411 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: Mozambique | Statement: [Zambia, borderedBy, Mozambique]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mozambique
Context triple: [Zambia, borderedBy, Mozambique]
  • A. Mozambique chosen
    Mozambique is a southeastern African nation on the Indian Ocean known for its Portuguese colonial heritage, rich cultural diversity, and extensive coastline with important ports and marine resources.
  • B. 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.
  • C. Tanzania
    Tanzania is an East African nation known for its vast wilderness areas, including the Serengeti National Park and Mount Kilimanjaro, as well as its rich cultural diversity.
  • D. Zambia
    Zambia is a landlocked country in south-central Africa known for the Victoria Falls on the Zambezi River, diverse wildlife, and copper-rich economy.
  • E. Angola
    Angola is a resource-rich country on Africa’s southwest coast, known for its oil and diamond industries and its history of a long civil war following independence.
  • 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_69a49389f44881909a608fb27d89f247 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abe6f0dc8190a1bebb5e21f4ceac completed March 1, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae26c4077081908dbf36ed274afa58 completed March 9, 2026, 1:47 a.m.
Created at: March 1, 2026, 7:38 p.m.