Triple

T18163133
Position Surface form Disambiguated ID Type / Status
Subject Martha Kearney E434817 entity
Predicate spouse P13 FINISHED
Object Chris Shaw
Chris Shaw is a British journalist and television executive, known for his work in UK broadcasting and as the husband of broadcaster Martha Kearney.
E1316496 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: Chris Shaw | Statement: [Martha Kearney, spouse, Chris Shaw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chris Shaw
Context triple: [Martha Kearney, spouse, Chris Shaw]
  • A. Chris Shaw
    Chris Shaw is an American professional baseball player and power-hitting outfielder/first baseman who played college baseball at Boston College before reaching Major League Baseball.
  • B. Chris Shaw
    Chris Shaw is a musician best known as a member of the garage rock band GØGGS.
  • C. Ian Shaw
    Ian Shaw is a British actor and writer, known for his stage and screen work and for being the son of acclaimed actor Robert Shaw.
  • D. Tom Shaw
    Tom Shaw is a central character in Louisa May Alcott’s novel "An Old-Fashioned Girl," portrayed as a kind but initially worldly young man whose growth and changing values mirror the story’s moral themes.
  • E. Mark Shaw
    Mark Shaw is best known as the husband of American singer and actress Pat Suzuki.
  • 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: Chris Shaw
Triple: [Martha Kearney, spouse, Chris Shaw]
Generated description
Chris Shaw is a British journalist and television executive, known for his work in UK broadcasting and as the husband of broadcaster Martha Kearney.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Chris Shaw
Target entity description: Chris Shaw is a British journalist and television executive, known for his work in UK broadcasting and as the husband of broadcaster Martha Kearney.
  • A. Chris Shaw
    Chris Shaw is an American professional baseball player and power-hitting outfielder/first baseman who played college baseball at Boston College before reaching Major League Baseball.
  • B. Chris Shaw
    Chris Shaw is a musician best known as a member of the garage rock band GØGGS.
  • C. Ian Shaw
    Ian Shaw is a British actor and writer, known for his stage and screen work and for being the son of acclaimed actor Robert Shaw.
  • D. Tom Shaw
    Tom Shaw is a central character in Louisa May Alcott’s novel "An Old-Fashioned Girl," portrayed as a kind but initially worldly young man whose growth and changing values mirror the story’s moral themes.
  • E. Mark Shaw
    Mark Shaw is best known as the husband of American singer and actress Pat Suzuki.
  • 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_69d8b90b7a188190b3fc7b8d4a6cd20a completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dec419788190a999a68f32fab39b completed April 19, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03bb453f808190a662038135968873 completed May 12, 2026, 11:44 p.m.
NEDg Description generation batch_6a03bc43edc48190965f07b9cedc23b6 completed May 12, 2026, 11:48 p.m.
NED2 Entity disambiguation (via description) batch_6a03bcda8dc88190a6dc4cff201d3ce6 completed May 12, 2026, 11:50 p.m.
Created at: April 10, 2026, 10:30 a.m.