Triple

T10605205
Position Surface form Disambiguated ID Type / Status
Subject Sarah Snook E275853 entity
Predicate spouse P13 FINISHED
Object Dave Lawson
Dave Lawson is an Australian comedian and actor known for his work in television, radio, and advertising, and for being married to actress Sarah Snook.
 E874124 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: Dave Lawson | Statement: [Sarah Snook, spouse, Dave Lawson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dave Lawson
Context triple: [Sarah Snook, spouse, Dave Lawson]
  • A. Sam Lawson
    Sam Lawson is a fictional New England storyteller created by Harriet Beecher Stowe, known for his humorous, dialect-rich tales in "Oldtown Fireside Stories."
  • B. Bill Lawson
    Bill Lawson was a boxing judge known for officiating the historic heavyweight title bout between Muhammad Ali and Sonny Liston.
  • C. Chris Lawler
    Chris Lawler is a former English footballer best known as a long-serving right-back for Liverpool FC during the 1960s and early 1970s.
  • D. Ben Lawson
    Ben Lawson is an Australian actor known for his roles in film and television, including the romantic comedy "No Strings Attached."
  • E. Brian Laws
    Brian Laws is an English former footballer and manager best known for his successful and lengthy spell in charge of Scunthorpe United.
  • 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: Dave Lawson
Triple: [Sarah Snook, spouse, Dave Lawson]
Generated description
Dave Lawson is an Australian comedian and actor known for his work in television, radio, and advertising, and for being married to actress Sarah Snook.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dave Lawson
Target entity description: Dave Lawson is an Australian comedian and actor known for his work in television, radio, and advertising, and for being married to actress Sarah Snook.
  • A. Sam Lawson
    Sam Lawson is a fictional New England storyteller created by Harriet Beecher Stowe, known for his humorous, dialect-rich tales in "Oldtown Fireside Stories."
  • B. Bill Lawson
    Bill Lawson was a boxing judge known for officiating the historic heavyweight title bout between Muhammad Ali and Sonny Liston.
  • C. Chris Lawler
    Chris Lawler is a former English footballer best known as a long-serving right-back for Liverpool FC during the 1960s and early 1970s.
  • D. Ben Lawson
    Ben Lawson is an Australian actor known for his roles in film and television, including the romantic comedy "No Strings Attached."
  • E. Brian Laws
    Brian Laws is an English former footballer and manager best known for his successful and lengthy spell in charge of Scunthorpe United.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df4a5df88190b993196ca7849a88 completed April 8, 2026, 11:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95eb726bc8190a8db7357bd126016 completed April 10, 2026, 8:33 p.m.
NEDg Description generation batch_69d95f81955c8190b629d57a034a4b76 completed April 10, 2026, 8:37 p.m.
NED2 Entity disambiguation (via description) batch_69d961047a78819088094e02c0b99f60 completed April 10, 2026, 8:43 p.m.
Created at: April 8, 2026, 7:32 p.m.