Triple

T5548865
Position Surface form Disambiguated ID Type / Status
Subject Narrow Bantu E145475 entity
Predicate includes P1393 FINISHED
Object Swahili language E2738 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: Swahili language | Statement: [Narrow Bantu, includes, Swahili language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swahili language
Context triple: [Narrow Bantu, includes, Swahili language]
  • A. Swahili language chosen
    Swahili is a major Bantu language widely spoken in East and Central Africa, serving as a regional lingua franca and an official language in several countries including Tanzania and Kenya.
  • B. Gikuyu
    Gikuyu is an alternative name for the Kikuyu, the largest ethnic group in Kenya known for their Bantu language and significant cultural and political influence in the country.
  • C. Nyamwezi language
    The Nyamwezi language is a Bantu language spoken primarily by the Nyamwezi people of western-central Tanzania.
  • D. Maasai language
    Maasai language is an Eastern Nilotic language spoken primarily by the Maasai people of Kenya and Tanzania, known for its rich oral tradition and distinctive phonology.
  • E. Ngindo language
    The Ngindo language is a Bantu language spoken by the Ngindo people of southeastern Tanzania.
  • 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_69c008fb879c81909f5bfa56fadc1d46 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01fe143ec8190bb67d2530c92a419 completed March 22, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0282dd7408190ad762fca9ff5e04b completed March 22, 2026, 5:34 p.m.
Created at: March 22, 2026, 3:35 p.m.