Triple

T14191567
Position Surface form Disambiguated ID Type / Status
Subject Sexy Beast E351724 entity
Predicate screenwriter P2831 FINISHED
Object David Scinto
David Scinto is a British screenwriter best known for co-writing the acclaimed crime film "Sexy Beast."
 E1086559 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: David Scinto | Statement: [Sexy Beast, screenwriter, David Scinto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: David Scinto
Context triple: [Sexy Beast, screenwriter, David Scinto]
  • A. Michael D’Orso
    Michael D’Orso is an American author and journalist known for co-writing influential nonfiction books, often chronicling social justice movements and notable public figures.
  • B. Jeff Kodosky
    Jeff Kodosky is an American engineer and co-founder of National Instruments, best known as the "father of LabVIEW" for creating the influential graphical programming environment.
  • C. Henry Ian Cusick
    Henry Ian Cusick is a Scottish-Peruvian actor best known for his roles on television series such as Lost and The 100.
  • D. Christopher Barreca
    Christopher Barreca is an American scenic designer known for his work on major stage productions, including the Broadway musical "Rocky."
  • E. David Reiman
    David Reiman is a researcher who contributed as a co-author to the landmark 2021 Nature paper by Jumper et al. describing the AlphaFold protein structure prediction system.
  • 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: David Scinto
Triple: [Sexy Beast, screenwriter, David Scinto]
Generated description
David Scinto is a British screenwriter best known for co-writing the acclaimed crime film "Sexy Beast."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: David Scinto
Target entity description: David Scinto is a British screenwriter best known for co-writing the acclaimed crime film "Sexy Beast."
  • A. Michael D’Orso
    Michael D’Orso is an American author and journalist known for co-writing influential nonfiction books, often chronicling social justice movements and notable public figures.
  • B. Jeff Kodosky
    Jeff Kodosky is an American engineer and co-founder of National Instruments, best known as the "father of LabVIEW" for creating the influential graphical programming environment.
  • C. Henry Ian Cusick
    Henry Ian Cusick is a Scottish-Peruvian actor best known for his roles on television series such as Lost and The 100.
  • D. Christopher Barreca
    Christopher Barreca is an American scenic designer known for his work on major stage productions, including the Broadway musical "Rocky."
  • E. David Reiman
    David Reiman is a researcher who contributed as a co-author to the landmark 2021 Nature paper by Jumper et al. describing the AlphaFold protein structure prediction system.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61df628c8190ba3f557e2128dce5 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd1946eb68819096adf3c16a39818d completed May 7, 2026, 10:59 p.m.
NEDg Description generation batch_69fd1eed1008819088635be43fbb1439 completed May 7, 2026, 11:23 p.m.
NED2 Entity disambiguation (via description) batch_69fd1f7c5d208190bab5d57e931fd082 completed May 7, 2026, 11:25 p.m.
Created at: April 10, 2026, 1:04 a.m.