Triple

T7747134
Position Surface form Disambiguated ID Type / Status
Subject Bailey Ndugu E175658 entity
Predicate hasLastName P18 FINISHED
Object Ndugu
Ndugu is a surname of likely African origin borne by various individuals, including those with the given name Bailey.
 E686132 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: Ndugu | Statement: [Bailey Ndugu, hasLastName, Ndugu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ndugu
Context triple: [Bailey Ndugu, hasLastName, Ndugu]
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Tunduma
    Tunduma is a border town in southern Tanzania that serves as a major road and rail gateway for trade and travel between Tanzania and Zambia.
  • C. Mungaka
    Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
  • D. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • E. Apswa
    Apswa is the endonym used by the Abkhaz people to refer to themselves and their language.
  • 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: Ndugu
Triple: [Bailey Ndugu, hasLastName, Ndugu]
Generated description
Ndugu is a surname of likely African origin borne by various individuals, including those with the given name Bailey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ndugu
Target entity description: Ndugu is a surname of likely African origin borne by various individuals, including those with the given name Bailey.
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Tunduma
    Tunduma is a border town in southern Tanzania that serves as a major road and rail gateway for trade and travel between Tanzania and Zambia.
  • C. Mungaka
    Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
  • D. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • E. Apswa
    Apswa is the endonym used by the Abkhaz people to refer to themselves and their language.
  • 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_69c69960b3588190a53aa590d31d9544 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7038caa64819084f61b42a73c2d8b completed March 27, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be50ac4881909b537f513bed2edd completed March 29, 2026, 5:53 a.m.
NEDg Description generation batch_69c8bf9e93bc8190a4764967c06de4af completed March 29, 2026, 5:58 a.m.
NED2 Entity disambiguation (via description) batch_69c8c01bf3f08190a0071eff2c412e6e completed March 29, 2026, 6:01 a.m.
Created at: March 27, 2026, 4:08 p.m.