Triple

T12990245
Position Surface form Disambiguated ID Type / Status
Subject Patrick Mboma E321883 entity
Predicate familyName P18 FINISHED
Object Mboma
Mboma is a Cameroonian surname most prominently associated with former international football striker Patrick Mboma.
 E1017810 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: Mboma | Statement: [Patrick Mboma, familyName, Mboma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mboma
Context triple: [Patrick Mboma, familyName, Mboma]
  • A. Mbato
    Mbato is a lesser-known Central Tano language spoken by a small community in West Africa, likely within the Ivory Coast–Ghana region.
  • B. Mohombi
    Mohombi is a Congolese-Swedish singer, songwriter, and dancer known for his international pop and dance hits blending African and European musical influences.
  • C. Mombo
    Mombo is a Dogon language variety spoken in Mali, known for its distinctive tonal system and role in the cultural identity of its speakers.
  • D. Mzembi
    Mzembi is the surname of Walter Mzembi, a Zimbabwean politician who served as Minister of Tourism and Hospitality Industry.
  • E. Mbala
    Mbala is a town in northern Zambia near the Tanzanian border, known historically as a colonial-era administrative center and for its proximity to Lake Tanganyika.
  • 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: Mboma
Triple: [Patrick Mboma, familyName, Mboma]
Generated description
Mboma is a Cameroonian surname most prominently associated with former international football striker Patrick Mboma.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mboma
Target entity description: Mboma is a Cameroonian surname most prominently associated with former international football striker Patrick Mboma.
  • A. Mbato
    Mbato is a lesser-known Central Tano language spoken by a small community in West Africa, likely within the Ivory Coast–Ghana region.
  • B. Mohombi
    Mohombi is a Congolese-Swedish singer, songwriter, and dancer known for his international pop and dance hits blending African and European musical influences.
  • C. Mombo
    Mombo is a Dogon language variety spoken in Mali, known for its distinctive tonal system and role in the cultural identity of its speakers.
  • D. Mzembi
    Mzembi is the surname of Walter Mzembi, a Zimbabwean politician who served as Minister of Tourism and Hospitality Industry.
  • E. Mbala
    Mbala is a town in northern Zambia near the Tanzanian border, known historically as a colonial-era administrative center and for its proximity to Lake Tanganyika.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e75b9f88190a54372c2a1223a4e completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbc277c881909ae77e8a44e06986 completed May 3, 2026, 4:14 a.m.
NEDg Description generation batch_69f6cea882d48190add88a8463f7d544 completed May 3, 2026, 4:27 a.m.
NED2 Entity disambiguation (via description) batch_69f6cf72a0cc8190bf8b6d606b8d0987 completed May 3, 2026, 4:30 a.m.
Created at: April 9, 2026, 8:43 p.m.