Triple

T9221868
Position Surface form Disambiguated ID Type / Status
Subject Susan Norton E221579 entity
Predicate associatedWith P37 FINISHED
Object Matt Burke
Matt Burke is a retired Australian rugby union player renowned for his long and successful career with the Wallabies and the New South Wales Waratahs, primarily as a fullback and goal-kicker.
 E814655 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: Matt Burke | Statement: [Susan Norton, associatedWith, Matt Burke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Matt Burke
Context triple: [Susan Norton, associatedWith, Matt Burke]
  • A. Dave Burke
    Dave Burke is a central character in the 1959 film noir "Odds Against Tomorrow," depicted as a former police officer who masterminds a high-stakes bank heist.
  • B. Mike Burrows
    Mike Burrows is a computer scientist best known for his influential work at Google on large-scale distributed systems, including co-authoring the Bigtable storage system.
  • C. Matt Curtis
    Matt Curtis is a cinematographer known for his work on the film "Amy."
  • D. Jim Burke
    Jim Burke is an American film producer known for his work on acclaimed movies such as "The Descendants" and "Green Book."
  • E. Sean Kilpatrick
    Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
  • 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: Matt Burke
Triple: [Susan Norton, associatedWith, Matt Burke]
Generated description
Matt Burke is a retired Australian rugby union player renowned for his long and successful career with the Wallabies and the New South Wales Waratahs, primarily as a fullback and goal-kicker.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Matt Burke
Target entity description: Matt Burke is a retired Australian rugby union player renowned for his long and successful career with the Wallabies and the New South Wales Waratahs, primarily as a fullback and goal-kicker.
  • A. Dave Burke
    Dave Burke is a central character in the 1959 film noir "Odds Against Tomorrow," depicted as a former police officer who masterminds a high-stakes bank heist.
  • B. Mike Burrows
    Mike Burrows is a computer scientist best known for his influential work at Google on large-scale distributed systems, including co-authoring the Bigtable storage system.
  • C. Matt Curtis
    Matt Curtis is a cinematographer known for his work on the film "Amy."
  • D. Jim Burke
    Jim Burke is an American film producer known for his work on acclaimed movies such as "The Descendants" and "Green Book."
  • E. Sean Kilpatrick
    Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
  • 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_69ca83ec8db08190a9110df8232885d2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda76e3648190af9e24381db7679a completed April 1, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69d190bef8548190a058e6014ff6690c completed April 4, 2026, 10:29 p.m.
NEDg Description generation batch_69d19327f0b481908be85bcb0deccb46 completed April 4, 2026, 10:39 p.m.
NED2 Entity disambiguation (via description) batch_69d193fac390819092dd913dc78e2841 completed April 4, 2026, 10:43 p.m.
Created at: March 30, 2026, 7:28 p.m.