Triple

T7854123
Position Surface form Disambiguated ID Type / Status
Subject Bantu E languages E182127 entity
Predicate hasMember P10 FINISHED
Object Rwanda-Rundi languages E617027 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: Rwanda-Rundi languages | Statement: [Bantu E languages, hasMember, Rwanda-Rundi languages]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rwanda-Rundi languages
Context triple: [Bantu E languages, hasMember, Rwanda-Rundi languages]
  • A. Kinyarwanda–Rundi languages chosen
    The Kinyarwanda–Rundi languages are a closely related cluster of Bantu languages spoken primarily in Rwanda and Burundi, including Kinyarwanda and Kirundi.
  • B. Kirundi
    Kirundi is a Bantu language primarily spoken in Burundi and neighboring regions of East Africa.
  • C. 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.
  • D. Kinyarwanda
    Kinyarwanda is a Bantu language spoken primarily in Rwanda, where it serves as a national and widely used lingua franca.
  • E. 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.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb1a72cfdc8190a3186c4c2894f571 completed March 31, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b1e9e808190a0eb2dea5288e743 completed March 31, 2026, 5:26 a.m.
Created at: March 30, 2026, 4:51 p.m.