Triple

T8801519
Position Surface form Disambiguated ID Type / Status
Subject Daniel arap Moi E209419 entity
Predicate familyName P18 FINISHED
Object Moi
Moi is a Kenyan surname most prominently associated with Daniel arap Moi, the long-serving second President of Kenya.
 E759357 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: Moi | Statement: [Daniel arap Moi, familyName, Moi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Moi
Context triple: [Daniel arap Moi, familyName, Moi]
  • A. Mina
    Mina is a valley and neighborhood near Mecca in Saudi Arabia that serves as a major site for key Hajj rituals, including the symbolic stoning of the devil.
  • B. Mina
    Mina is a Gbe language of the Niger-Congo family spoken primarily in southern Togo and neighboring regions of West Africa.
  • C. Mina
    Mina is a coastal city and port in northern Lebanon known for its maritime activities and proximity to Tripoli.
  • D. Moji
    Moji was a former city in Fukuoka Prefecture, Japan, that later became a ward of Kitakyushu and is known for its historic port and preserved retro district.
  • E. Mio
    Mio is the Japanese-led Mercury Magnetospheric Orbiter, a component of the joint ESA–JAXA BepiColombo mission designed to study Mercury’s magnetic field and space environment.
  • 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: Moi
Triple: [Daniel arap Moi, familyName, Moi]
Generated description
Moi is a Kenyan surname most prominently associated with Daniel arap Moi, the long-serving second President of Kenya.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Moi
Target entity description: Moi is a Kenyan surname most prominently associated with Daniel arap Moi, the long-serving second President of Kenya.
  • A. Mina
    Mina is a valley and neighborhood near Mecca in Saudi Arabia that serves as a major site for key Hajj rituals, including the symbolic stoning of the devil.
  • B. Mina
    Mina is a Gbe language of the Niger-Congo family spoken primarily in southern Togo and neighboring regions of West Africa.
  • C. Mina
    Mina is a coastal city and port in northern Lebanon known for its maritime activities and proximity to Tripoli.
  • D. Moji
    Moji was a former city in Fukuoka Prefecture, Japan, that later became a ward of Kitakyushu and is known for its historic port and preserved retro district.
  • E. Mio
    Mio is the Japanese-led Mercury Magnetospheric Orbiter, a component of the joint ESA–JAXA BepiColombo mission designed to study Mercury’s magnetic field and space environment.
  • 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_69ca836320e48190b5cf585b90a322c4 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fb9c5c88190881b069e1face10c completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f6fdd688190bf40bbde0be991e1 completed April 3, 2026, 7:42 a.m.
NEDg Description generation batch_69cf718a6f2c81908f8b8d08a1437749 completed April 3, 2026, 7:51 a.m.
NED2 Entity disambiguation (via description) batch_69cf7275fea08190b8999fb30663ff17 completed April 3, 2026, 7:55 a.m.
Created at: March 30, 2026, 6:44 p.m.