Triple

T1187744
Position Surface form Disambiguated ID Type / Status
Subject Bantu languages E25285 entity
Predicate majorLanguage P207 FINISHED
Object Kiswahili 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: Kiswahili | Statement: [Bantu languages, majorLanguage, Kiswahili]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiswahili
Context triple: [Bantu languages, majorLanguage, Kiswahili]
  • 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. Chichewa
    Chichewa is a major Bantu language spoken primarily in Malawi and neighboring countries, serving as a national and widely used lingua franca in the region.
  • C. Luganda
    Luganda is a major Bantu language spoken primarily in Uganda, serving as a key lingua franca and cultural language of the Baganda people.
  • 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. Kirundi
    Kirundi is a Bantu language primarily spoken in Burundi and neighboring regions of East Africa.
  • 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd568cf481908d10cf19a3ce28f3 completed March 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f36371c8190a656463a9ae6402a completed March 7, 2026, 7:40 p.m.
Created at: March 1, 2026, 7:45 p.m.