Triple

T10582192
Position Surface form Disambiguated ID Type / Status
Subject Munukutuba E249762 entity
Predicate hasAncestor P369 FINISHED
Object Kongo language E57354 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: Kongo language | Statement: [Munukutuba, hasAncestor, Kongo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kongo language
Context triple: [Munukutuba, hasAncestor, Kongo language]
  • A. Konongo language
    The Konongo language is a Bantu language of East Africa, closely related to Sukuma and spoken by the Konongo people.
  • B. Kongo languages
    Kongo languages are a group of closely related Bantu languages spoken primarily in the Democratic Republic of the Congo, Angola, and the Republic of the Congo, known for including the widely used Kikongo.
  • C. Kikongo chosen
    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.
  • D. Luba languages
    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.
  • E. Kwango-Kwilu languages
    The Kwango-Kwilu languages are a subgroup of Bantu languages spoken primarily in the Kwango and Kwilu river regions of the Democratic Republic of the Congo and neighboring areas.
  • 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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d52766d53c8190b51753768ab58c31 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b78ff28819085acf84418d54733 completed April 10, 2026, 7:11 p.m.
Created at: April 6, 2026, 12:39 p.m.