Triple

T12545689
Position Surface form Disambiguated ID Type / Status
Subject Sheku Kanneh-Mason E299963 entity
Predicate givenName P17 FINISHED
Object Sheku
Sheku is a British cellist renowned for his expressive performances and for rising to international prominence after winning the BBC Young Musician of the Year award.
 E988842 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: Sheku | Statement: [Sheku Kanneh-Mason, givenName, Sheku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sheku
Context triple: [Sheku Kanneh-Mason, givenName, Sheku]
  • A. Balewa Muhammad
    Balewa Muhammad is a songwriter best known for co-writing Christina Aguilera’s hit single "Dirrty."
  • B. Musa
    Musa is a central character in Arundhati Roy’s novel "The Ministry of Utmost Happiness," around whom key political and personal conflicts in Kashmir revolve.
  • C. Musa
    Musa is a genus of large herbaceous flowering plants that includes the bananas and plantains widely cultivated for their edible fruit.
  • D. Musa
    Musa is the name used in the Quran for the prophet Moses, a central figure in Islamic tradition known for leading the Israelites and receiving divine revelation.
  • E. Jayhun
    Jayhun is the historical name used in Islamic and Persian sources for the Amu Darya, one of Central Asia’s major rivers.
  • 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: Sheku
Triple: [Sheku Kanneh-Mason, givenName, Sheku]
Generated description
Sheku is a British cellist renowned for his expressive performances and for rising to international prominence after winning the BBC Young Musician of the Year award.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sheku
Target entity description: Sheku is a British cellist renowned for his expressive performances and for rising to international prominence after winning the BBC Young Musician of the Year award.
  • A. Balewa Muhammad
    Balewa Muhammad is a songwriter best known for co-writing Christina Aguilera’s hit single "Dirrty."
  • B. Musa
    Musa is a central character in Arundhati Roy’s novel "The Ministry of Utmost Happiness," around whom key political and personal conflicts in Kashmir revolve.
  • C. Musa
    Musa is the name used in the Quran for the prophet Moses, a central figure in Islamic tradition known for leading the Israelites and receiving divine revelation.
  • D. Musa
    Musa is a genus of large herbaceous flowering plants that includes the bananas and plantains widely cultivated for their edible fruit.
  • E. Jayhun
    Jayhun is the historical name used in Islamic and Persian sources for the Amu Darya, one of Central Asia’s major rivers.
  • 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_69d6ada707008190aaec1238117c9379 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9547f9a1c81908f54c58a116a8446 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f655801cac8190b1f9a72f8fed0399 completed May 2, 2026, 7:50 p.m.
NEDg Description generation batch_69f6566f40c08190baec227fb660c948 completed May 2, 2026, 7:54 p.m.
NED2 Entity disambiguation (via description) batch_69f657aec8fc8190b3b08ccb95595958 completed May 2, 2026, 7:59 p.m.
Created at: April 8, 2026, 9:57 p.m.