Triple

T18241516
Position Surface form Disambiguated ID Type / Status
Subject Tracy Kidder E436823 entity
Predicate hasGivenName P17 FINISHED
Object John
John is the given first name of the American author and Pulitzer Prize–winning journalist Tracy Kidder.
E436823 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: John | Statement: [Tracy Kidder, hasGivenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [Tracy Kidder, hasGivenName, John]
  • A. John
    John is the nickname of John Riggins, a former American football running back best known for his Hall of Fame career with the Washington Redskins in the NFL.
  • B. John
    John is the given name of John Reith, the influential first Director-General of the BBC who shaped early public service broadcasting in the United Kingdom.
  • C. John
    John is the given name of John Boyd-Carpenter, a prominent British Conservative politician who served in several senior government positions in the mid-20th century.
  • D. John
    John is the first name of John Dashwood, a character in Jane Austen's novel "Sense and Sensibility."
  • E. John
    John is the first name of the fictional character John Connor, the prophesied leader of the human resistance in the Terminator franchise.
  • 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: John
Triple: [Tracy Kidder, hasGivenName, John]
Generated description
John is the given first name of the American author and Pulitzer Prize–winning journalist Tracy Kidder.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given first name of the American author and Pulitzer Prize–winning journalist Tracy Kidder.
  • A. John chosen
    John is the first name of American author and Pulitzer Prize winner Tracy Kidder, known for his works of literary nonfiction.
  • B. John
    John is the given name of the renowned American author John Steinbeck, known for works such as "The Grapes of Wrath" and "Of Mice and Men."
  • C. John
    John is the given name of John Hersey, the American writer and journalist renowned for his groundbreaking reportage on the aftermath of the Hiroshima bombing.
  • D. John
    John is the first name of the American author and filmmaker Michael Crichton, known for works like "Jurassic Park" and "The Andromeda Strain."
  • E. John
    John is the given name of the American novelist, short-story writer, and critic John Updike, renowned for his insightful portrayals of middle-class American life.
  • F. None of above.

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_69d8b91104e08190a8241f7d260a5162 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f7e387f481909d72574fb7d17923 completed April 19, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03ac651d3481908651893456104d96 completed May 12, 2026, 10:40 p.m.
NEDg Description generation batch_6a03ad9fce588190aefc253355b124de completed May 12, 2026, 10:45 p.m.
NED2 Entity disambiguation (via description) batch_6a03aebcd61881909e1c69427502ecc1 completed May 12, 2026, 10:50 p.m.
Created at: April 10, 2026, 10:33 a.m.