Triple

T14607048
Position Surface form Disambiguated ID Type / Status
Subject Muhammadu Bello E342857 entity
Predicate familyName P18 FINISHED
Object Bello
Bello is a common surname of Hausa and broader West African origin, notably borne by several prominent Nigerian leaders and public figures.
 E1108304 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: Bello | Statement: [Muhammadu Bello, familyName, Bello]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bello
Context triple: [Muhammadu Bello, familyName, Bello]
  • A. Bello
    Bello is a Colombian city in the Aburrá Valley metropolitan area, just north of Medellín, known for its industrial activity and dense urban development.
  • B. Bonomi
    Bonomi is an Italian surname most notably associated with Ivanoe Bonomi, a prominent early 20th-century Italian politician and statesman.
  • C. Belli
    The Belli were a prominent ancient Celtiberian tribe inhabiting the central-eastern Iberian Peninsula, known for their role in conflicts with Rome during the 2nd century BCE.
  • D. Bela
    Bela is a historic town in Pakistan’s Balochistan province, known as an administrative and commercial center within the Lasbela region.
  • E. Bela
    Bela is a supporting character in the 1941 horror film "The Wolf Man," portrayed as a tormented Romani werewolf whose curse sets the story’s tragic events in motion.
  • 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: Bello
Triple: [Muhammadu Bello, familyName, Bello]
Generated description
Bello is a common surname of Hausa and broader West African origin, notably borne by several prominent Nigerian leaders and public figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bello
Target entity description: Bello is a common surname of Hausa and broader West African origin, notably borne by several prominent Nigerian leaders and public figures.
  • A. Bello
    Bello is a Colombian city in the Aburrá Valley metropolitan area, just north of Medellín, known for its industrial activity and dense urban development.
  • B. Bonomi
    Bonomi is an Italian surname most notably associated with Ivanoe Bonomi, a prominent early 20th-century Italian politician and statesman.
  • C. Belli
    The Belli were a prominent ancient Celtiberian tribe inhabiting the central-eastern Iberian Peninsula, known for their role in conflicts with Rome during the 2nd century BCE.
  • D. Bela
    Bela is a historic town in Pakistan’s Balochistan province, known as an administrative and commercial center within the Lasbela region.
  • E. Bela
    Bela is a supporting character in the 1941 horror film "The Wolf Man," portrayed as a tormented Romani werewolf whose curse sets the story’s tragic events in motion.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44d327c8190a8d20568429d0f80 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94d09e988190a2a2a1332397b412 completed May 8, 2026, 7:46 a.m.
NEDg Description generation batch_69fd9828129c8190bd7445e99dadc618 completed May 8, 2026, 8 a.m.
NED2 Entity disambiguation (via description) batch_69fd98cf0bcc81909dac826a32daaf04 completed May 8, 2026, 8:03 a.m.
Created at: April 10, 2026, 1:25 a.m.