Triple

T2818101
Position Surface form Disambiguated ID Type / Status
Subject Tshiluba E54338 entity
Predicate hasDialects P4251 FINISHED
Object Western Tshiluba E300902 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: Western Tshiluba | Statement: [Tshiluba, hasDialects, Western Tshiluba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Western Tshiluba
Context triple: [Tshiluba, hasDialects, Western Tshiluba]
  • A. Luba languages chosen
    The Luba languages are a group of closely related Bantu languages spoken primarily in the Democratic Republic of the Congo by the Luba people and neighboring communities.
  • B. Kikongo
    Kikongo is a Bantu language widely spoken in Central Africa, particularly in the western regions of the Democratic Republic of the Congo and neighboring countries.
  • C. Tumbuka
    Tumbuka is a Bantu language spoken primarily in northern Malawi and parts of Zambia and Tanzania.
  • D. Northwest Bantu
    Northwest Bantu is a subgroup of Bantu languages spoken in parts of Central and West-Central Africa, encompassing languages such as Fang.
  • E. Lingala
    Lingala is a Bantu language widely spoken as a lingua franca in the Democratic Republic of the Congo and the Republic of the Congo, especially in urban centers and along the Congo River.
  • 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_69ab49de0af08190b3da69683be1e728 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde6c44d881909f8275b6466e2f20 completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8b344ec8190948b26a5101fb183 completed March 10, 2026, 9:47 a.m.
Created at: March 6, 2026, 9:59 p.m.