Triple

T1820652
Position Surface form Disambiguated ID Type / Status
Subject Nobiin E40530 entity
Predicate closelyRelatedTo P37 FINISHED
Object Kenzi
Kenzi is a Nubian language spoken in southern Egypt, closely related to Nobiin and part of the broader Nubian language family along the Nile.
 E202800 NE FINISHED

How this triple was built (4 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: Kenzi | Statement: [Nobiin, closelyRelatedTo, Kenzi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kenzi
Context triple: [Nobiin, closelyRelatedTo, Kenzi]
  • A. Dongo
    Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
  • B. Mukuzani
    Mukuzani is a renowned Georgian red wine appellation known for producing dry, oak-aged wines from the Saperavi grape in the Kakheti region.
  • C. Tuka
    Tuka is the affectionate self-referential name used by the 17th-century Marathi saint-poet Tukaram in his devotional abhangas.
  • D. Tuka
    Tuka is a surname most notably associated with Vojtech Tuka, a Slovak politician and leading figure of the World War II-era Slovak State.
  • E. Mizani
    Mizani is a professional haircare brand known for its salon-quality products formulated specifically for textured, curly, and coily hair.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kenzi
Triple: [Nobiin, closelyRelatedTo, Kenzi]
Generated description
Kenzi is a Nubian language spoken in southern Egypt, closely related to Nobiin and part of the broader Nubian language family along the Nile.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kenzi
Target entity description: Kenzi is a Nubian language spoken in southern Egypt, closely related to Nobiin and part of the broader Nubian language family along the Nile.
  • A. Dongo
    Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
  • B. Mukuzani
    Mukuzani is a renowned Georgian red wine appellation known for producing dry, oak-aged wines from the Saperavi grape in the Kakheti region.
  • C. Tuka
    Tuka is the affectionate self-referential name used by the 17th-century Marathi saint-poet Tukaram in his devotional abhangas.
  • D. Tuka
    Tuka is a surname most notably associated with Vojtech Tuka, a Slovak politician and leading figure of the World War II-era Slovak State.
  • E. Mizani
    Mizani is a professional haircare brand known for its salon-quality products formulated specifically for textured, curly, and coily hair.
  • F. None of above. chosen

Provenance (5 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_69a8864526c081908a3a4d74f689e2c5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa662a13208190b4126d92c613760d completed March 6, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf6526f88190907de68a5344a084 completed March 8, 2026, 6:26 p.m.
NEDg Description generation batch_69adbff32038819088dffc71e8376821 completed March 8, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_69adc084c9b88190a0d53f5c7c459611 completed March 8, 2026, 6:31 p.m.
Created at: March 4, 2026, 7:32 p.m.