Triple

T12782909
Position Surface form Disambiguated ID Type / Status
Subject Real Life E305550 entity
Predicate stars P1956 FINISHED
Object Matthew Tobin
Matthew Tobin is an actor known for his role in the film "Real Life."
E1038673 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: Matthew Tobin | Statement: [Real Life, stars, Matthew Tobin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Tobin
Context triple: [Real Life, stars, Matthew Tobin]
  • A. Patrick Tobin
    Patrick Tobin is an American screenwriter best known for writing the screenplay for the 2014 drama film "Cake" starring Jennifer Aniston.
  • B. Matthew McNulty
    Matthew McNulty is a British actor known for his work in film and television, including roles in series like "Misfits," "The Mill," and "Versailles."
  • C. Toby Neary
    Toby Neary is a fictional character appearing as one of Roy Neary’s children in the science fiction film "Close Encounters of the Third Kind."
  • D. Sean Kilpatrick
    Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
  • E. Michael McCusker
    Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
  • 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: Matthew Tobin
Triple: [Real Life, stars, Matthew Tobin]
Generated description
Matthew Tobin is an actor known for his role in the film "Real Life."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matthew Tobin
Target entity description: Matthew Tobin is an actor known for his role in the film "Real Life."
  • A. Patrick Tobin
    Patrick Tobin is an American screenwriter best known for writing the screenplay for the 2014 drama film "Cake" starring Jennifer Aniston.
  • B. Matthew McNulty
    Matthew McNulty is a British actor known for his work in film and television, including roles in series like "Misfits," "The Mill," and "Versailles."
  • C. Toby Neary
    Toby Neary is a fictional character appearing as one of Roy Neary’s children in the science fiction film "Close Encounters of the Third Kind."
  • D. Sean Kilpatrick
    Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
  • E. Michael McCusker
    Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e5b52048190b279b7ad066efe9f completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7304f62288190aa7788fc6fb04254 completed May 3, 2026, 11:23 a.m.
NEDg Description generation batch_69f7316101e48190b3ec59a4376a0562 completed May 3, 2026, 11:28 a.m.
NED2 Entity disambiguation (via description) batch_69f731f8e98c8190becfad8e3a371484 completed May 3, 2026, 11:31 a.m.
Created at: April 9, 2026, 5:29 p.m.