Triple

T12715864
Position Surface form Disambiguated ID Type / Status
Subject Mayorkun E303835 entity
Predicate notableWork P4 FINISHED
Object Geng
Geng is a popular Afrobeats song by Nigerian singer Mayorkun, known for its catchy hook and energetic, street-influenced vibe.
 E997416 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: Geng | Statement: [Mayorkun, notableWork, Geng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Geng
Context triple: [Mayorkun, notableWork, Geng]
  • A. Gengbe
    Gengbe is a dialect of the Gbe language cluster spoken primarily in parts of West Africa, closely related to Ewe and other Gbe varieties.
  • B. Guan
    Guan is a common Chinese surname with historical roots and multiple romanized variants, including Kwan.
  • C. Suo-Gân
    Suo-Gân is a traditional Welsh lullaby known for its gentle melody and soothing, lyrical character.
  • D. Gento
    Gento was a Vandal nobleman of the late 5th century, known primarily as a member of the Vandal royal family in North Africa.
  • E. Genda
    Genda is a Japanese surname most notably associated with Minoru Genda, an Imperial Japanese Navy officer and key planner of the attack on Pearl Harbor.
  • 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: Geng
Triple: [Mayorkun, notableWork, Geng]
Generated description
Geng is a popular Afrobeats song by Nigerian singer Mayorkun, known for its catchy hook and energetic, street-influenced vibe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Geng
Target entity description: Geng is a popular Afrobeats song by Nigerian singer Mayorkun, known for its catchy hook and energetic, street-influenced vibe.
  • A. Gengbe
    Gengbe is a dialect of the Gbe language cluster spoken primarily in parts of West Africa, closely related to Ewe and other Gbe varieties.
  • B. Guan
    Guan is a common Chinese surname with historical roots and multiple romanized variants, including Kwan.
  • C. Suo-Gân
    Suo-Gân is a traditional Welsh lullaby known for its gentle melody and soothing, lyrical character.
  • D. Gento
    Gento was a Vandal nobleman of the late 5th century, known primarily as a member of the Vandal royal family in North Africa.
  • E. Genda
    Genda is a Japanese surname most notably associated with Minoru Genda, an Imperial Japanese Navy officer and key planner of the attack on Pearl Harbor.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9620bd6148190a2f50067a4c18c14 completed April 10, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671bad5108190915d14c3ec3d2e27 completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f67286f1b8819081db3da2f5c16daf completed May 2, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_69f67323a724819092425cdb3a070b96 completed May 2, 2026, 9:56 p.m.
Created at: April 9, 2026, 5:23 p.m.