Triple

T14228788
Position Surface form Disambiguated ID Type / Status
Subject Zimbabwe–South Africa border E352695 entity
Predicate hasLanguageInBorderRegion P54485 FINISHED
Object Venda E52951 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: Venda | Statement: [Zimbabwe–South Africa border, hasLanguageInBorderRegion, Venda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Venda
Context triple: [Zimbabwe–South Africa border, hasLanguageInBorderRegion, Venda]
  • A. Venda chosen
    Venda is a Bantu language of the Venda people of South Africa and Zimbabwe, recognized as one of South Africa’s official languages.
  • B. Loja
    Loja is a city in southern Ecuador known as a cultural and musical center nestled in the Andean highlands.
  • C. Loja
    Loja is a historic town in the province of Granada, Spain, known for its strategic location between Granada and the coast and its role in the final stages of the Reconquista.
  • D. Feira Nova
    Feira Nova is a small municipality located in the semi-arid interior region of the state of Sergipe, Brazil.
  • E. Beli
    Beli is a small village and historic settlement located on the Croatian island of Cres in the Adriatic Sea.
  • 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_69fd2819bfec8190b555632338c53740 completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:07 a.m.