Triple

T671673
Position Surface form Disambiguated ID Type / Status
Subject Class E12983 entity
Predicate featuresActor P15562 FINISHED
Object Jordan Renzo
Jordan Renzo is a British actor known for his roles in film and television, including appearances in series such as "The Witcher."
 E87220 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: Jordan Renzo | Statement: [Class, featuresActor, Jordan Renzo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jordan Renzo
Context triple: [Class, featuresActor, Jordan Renzo]
  • A. Robby Mook
    Robby Mook is an American political strategist best known for serving as campaign manager for Hillary Clinton’s 2016 U.S. presidential campaign.
  • B. Michael Convertino
    Michael Convertino is an American film composer known for scoring a variety of movies and television projects.
  • C. Dante Spinotti
    Dante Spinotti is an acclaimed Italian cinematographer known for his visually distinctive work on films such as Heat, L.A. Confidential, and The Insider.
  • D. Jake Nava
    Jake Nava is a British music video director known for his visually striking work with major artists across pop and R&B.
  • E. Fran Fraschilla
    Fran Fraschilla is an American basketball coach and ESPN analyst best known for his successful college coaching stints and his expertise on international basketball.
  • 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: Jordan Renzo
Triple: [Class, featuresActor, Jordan Renzo]
Generated description
Jordan Renzo is a British actor known for his roles in film and television, including appearances in series such as "The Witcher."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jordan Renzo
Target entity description: Jordan Renzo is a British actor known for his roles in film and television, including appearances in series such as "The Witcher."
  • A. Robby Mook
    Robby Mook is an American political strategist best known for serving as campaign manager for Hillary Clinton’s 2016 U.S. presidential campaign.
  • B. Michael Convertino
    Michael Convertino is an American film composer known for scoring a variety of movies and television projects.
  • C. Dante Spinotti
    Dante Spinotti is an acclaimed Italian cinematographer known for his visually distinctive work on films such as Heat, L.A. Confidential, and The Insider.
  • D. Jake Nava
    Jake Nava is a British music video director known for his visually striking work with major artists across pop and R&B.
  • E. Fran Fraschilla
    Fran Fraschilla is an American basketball coach and ESPN analyst best known for his successful college coaching stints and his expertise on international basketball.
  • 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_69a493355dec819098d4244b2fa34885 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a518e6348190b467c2fab3fd1f11 completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6374a189c81908f7bc0828e9ff382 completed March 3, 2026, 1:20 a.m.
NEDg Description generation batch_69a647001b4481909654167ccfe6f434 completed March 3, 2026, 2:27 a.m.
NED2 Entity disambiguation (via description) batch_69a6476b3a048190a80683422d29befd completed March 3, 2026, 2:28 a.m.
Created at: March 1, 2026, 7:36 p.m.