Triple

T18710300
Position Surface form Disambiguated ID Type / Status
Subject Matt Gerald E457487 entity
Predicate portrayed P1668 FINISHED
Object Darnell
Darnell is a fictional character played by American actor Matt Gerald, known for his tough, often antagonistic roles in film and television.
 E1338805 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: Darnell | Statement: [Matt Gerald, portrayed, Darnell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Darnell
Context triple: [Matt Gerald, portrayed, Darnell]
  • A. Darnell
    Darnell is a surname of English origin borne by various notable individuals, including the American actress Linda Darnell.
  • B. Darell
    Darell is a surname most notably associated with characters in Isaac Asimov’s Foundation series, including the psychohistorian Bayta Darell.
  • C. Darell
    Darell is a Puerto Rican reggaeton and Latin trap singer and rapper known for his collaborations on major urban Latin hits.
  • D. Darnell Lewis
    Darnell Lewis is a central comedic character in the film "Get Hard," portrayed as a small-business owner who helps a wealthy, naive financier prepare for prison life.
  • E. Denzell
    Denzell is a given name that serves as an alternative spelling of the more common name Denzel.
  • 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: Darnell
Triple: [Matt Gerald, portrayed, Darnell]
Generated description
Darnell is a fictional character played by American actor Matt Gerald, known for his tough, often antagonistic roles in film and television.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Darnell
Target entity description: Darnell is a fictional character played by American actor Matt Gerald, known for his tough, often antagonistic roles in film and television.
  • A. Darnell
    Darnell is a surname of English origin borne by various notable individuals, including the American actress Linda Darnell.
  • B. Darell
    Darell is a surname most notably associated with characters in Isaac Asimov’s Foundation series, including the psychohistorian Bayta Darell.
  • C. Darell
    Darell is a Puerto Rican reggaeton and Latin trap singer and rapper known for his collaborations on major urban Latin hits.
  • D. Darnell Lewis
    Darnell Lewis is a central comedic character in the film "Get Hard," portrayed as a small-business owner who helps a wealthy, naive financier prepare for prison life.
  • E. Denzell
    Denzell is a given name that serves as an alternative spelling of the more common name Denzel.
  • 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5671a3c8c81909466bf5d81477a37 completed April 19, 2026, 11:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a052b3f247c8190922c4ce9f67301a0 completed May 14, 2026, 1:54 a.m.
NEDg Description generation batch_6a052c6373088190a81e53963dac9c6f completed May 14, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_6a052d6f1f8081908810e99dff28b586 completed May 14, 2026, 2:03 a.m.
Created at: April 10, 2026, 11:50 a.m.