Triple

T296053
Position Surface form Disambiguated ID Type / Status
Subject Idris Elba E6094 entity
Predicate givenName P17 FINISHED
Object Idrissa
Idrissa is the given first name of British actor, producer, and musician Idris Elba.
E38384 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: Idrissa | Statement: [Idris Elba, givenName, Idrissa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Idrissa
Context triple: [Idris Elba, givenName, Idrissa]
  • A. Bambara
    Bambara is a major Mande language widely spoken in Mali and neighboring West African countries, serving as a key lingua franca in the region.
  • B. Abdul Salaam
    Abdul Salaam is a former American football defensive tackle best known as a member of the New York Jets' famed "New York Sack Exchange" defensive line in the late 1970s and early 1980s.
  • C. Nasar
    Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
  • D. Mandinka
    Mandinka is a major Mande language spoken primarily in The Gambia, Senegal, Guinea-Bissau, and neighboring West African countries by the Mandinka people.
  • E. Monsieur Ibrahim
    Monsieur Ibrahim is a 2003 French drama film in which Omar Sharif delivers an acclaimed performance as a wise Turkish shopkeeper who befriends a lonely Parisian boy.
  • 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: Idrissa
Triple: [Idris Elba, givenName, Idrissa]
Generated description
Idrissa is the given first name of British actor, producer, and musician Idris Elba.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Idrissa
Target entity description: Idrissa is the given first name of British actor, producer, and musician Idris Elba.
  • A. Bambara
    Bambara is a major Mande language widely spoken in Mali and neighboring West African countries, serving as a key lingua franca in the region.
  • B. Abdul Salaam
    Abdul Salaam is a former American football defensive tackle best known as a member of the New York Jets' famed "New York Sack Exchange" defensive line in the late 1970s and early 1980s.
  • C. Nasar
    Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
  • D. Mandinka
    Mandinka is a major Mande language spoken primarily in The Gambia, Senegal, Guinea-Bissau, and neighboring West African countries by the Mandinka people.
  • E. Monsieur Ibrahim
    Monsieur Ibrahim is a 2003 French drama film in which Omar Sharif delivers an acclaimed performance as a wise Turkish shopkeeper who befriends a lonely Parisian boy.
  • 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_69a2e79114b081909490b3bf5a5dbb51 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2e979663481908cf9622e59fed041 completed Feb. 28, 2026, 1:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3a88778b48190856af2e89d21621a completed March 1, 2026, 2:46 a.m.
NEDg Description generation batch_69a3a8f94d848190ad2410b5f8f8f79d completed March 1, 2026, 2:48 a.m.
NED2 Entity disambiguation (via description) batch_69a3a96d153081909fab6bace45206ec completed March 1, 2026, 2:50 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.