Triple

T6710851
Position Surface form Disambiguated ID Type / Status
Subject Southern Bantu languages E153135 entity
Predicate spokenIn P2266 FINISHED
Object Eswatini E16080 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: Eswatini | Statement: [Southern Bantu languages, spokenIn, Eswatini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eswatini
Context triple: [Southern Bantu languages, spokenIn, Eswatini]
  • A. Eswatini chosen
    Eswatini is a small landlocked monarchy in Southern Africa known for its blend of traditional Swazi culture and modern institutions.
  • B. Lesotho
    Lesotho is a small, landlocked constitutional monarchy in Southern Africa, entirely surrounded by South Africa and known for its mountainous terrain and high-altitude settlements.
  • C. Botswana
    Botswana is a landlocked country in Southern Africa known for its stable democracy, significant diamond resources, and vast wildlife-rich landscapes including the Okavango Delta.
  • D. Siphofaneni, Eswatini
    Siphofaneni is a rural town in central Eswatini known as an agricultural and transport hub situated near the Great Usutu River.
  • E. 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.
  • 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_69c70af508388190866e6452443dc9ff completed March 27, 2026, 10:55 p.m.
Created at: March 27, 2026, 2:06 p.m.