Triple

T6710865
Position Surface form Disambiguated ID Type / Status
Subject Southern Bantu languages E153135 entity
Predicate includesLanguage P2177 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: [Southern Bantu languages, includesLanguage, Venda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Venda
Context triple: [Southern Bantu languages, includesLanguage, 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. Vendas Novas
    Vendas Novas is a Portuguese town and municipality in the Alentejo region, known for its strategic location between Lisbon and Évora and its traditional bifanas (pork sandwiches).
  • E. Feira Nova
    Feira Nova is a small municipality located in the semi-arid interior region of the state of Sergipe, Brazil.
  • 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_69c68808d8d8819087369015270788fe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d107380481909cc761dc182834c1 completed March 27, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c700906a9c81908a121db4291195d8 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:06 p.m.