Triple

T2734605
Position Surface form Disambiguated ID Type / Status
Subject Dongolawi E60598 entity
Predicate closelyRelatedTo P37 FINISHED
Object Kenuzi-Dongola E255790 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: Kenuzi-Dongola | Statement: [Dongolawi, closelyRelatedTo, Kenuzi-Dongola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenuzi-Dongola
Context triple: [Dongolawi, closelyRelatedTo, Kenuzi-Dongola]
  • A. Kenuzi-Dongola chosen
    Kenuzi-Dongola is a Nubian language of the Eastern Sudanic branch spoken primarily along the Nile in southern Egypt and northern Sudan.
  • B. Dongola
    Dongola is a historic town in northern Sudan that served as a major political and cultural center of medieval Nubian kingdoms along the Nile.
  • C. Dinka
    Dinka is a Nilotic language spoken primarily by the Dinka people of South Sudan.
  • D. Anseba
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • E. Al-Khartum Bahri
    Al-Khartum Bahri is the Arabic name for Khartoum North, a major city and industrial hub forming part of Sudan’s capital metropolitan area.
  • 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_69ab4b77febc819095603eb012cd141b completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb0e7b888190bfa5d2e33f00ec0f completed March 7, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbc430ec8190a54f805cd0067b97 completed March 10, 2026, 6:35 a.m.
Created at: March 6, 2026, 9:56 p.m.