Triple

T5056882
Position Surface form Disambiguated ID Type / Status
Subject George S. Kaufman E113923 entity
Predicate givenName P17 FINISHED
Object George
George is the given name of George S. Kaufman, the prominent American playwright, director, and humorist.
E372350 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: George | Statement: [George S. Kaufman, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [George S. Kaufman, givenName, George]
  • A. George
    George is the heroic protagonist of the fantasy film "The Magic Sword," known for embarking on a perilous quest to rescue a princess from an evil sorcerer.
  • B. George
    George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
  • C. George
    George is a town in South Africa’s Western Cape province, known as a gateway to the Garden Route and for its scenic mountains and forests.
  • D. George
    George is one of the central child detectives in Enid Blyton’s classic Secret Seven mystery series.
  • E. George
    George is the birth name of the legendary American baseball player Babe Ruth, one of the sport’s most iconic figures.
  • 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: George
Triple: [George S. Kaufman, givenName, George]
Generated description
George is the given name of George S. Kaufman, the prominent American playwright, director, and humorist.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: George
Target entity description: George is the given name of George S. Kaufman, the prominent American playwright, director, and humorist.
  • A. George chosen
    George is a male given name commonly used in English-speaking countries and borne by numerous historical figures, including kings, presidents, and cultural icons.
  • B. George
    George is the birth name of the legendary American baseball player Babe Ruth, one of the sport’s most iconic figures.
  • C. George
    George is the given name of George Bellas Greenough, a pioneering 19th-century English geologist and founding figure of the Geological Society of London.
  • D. George
    George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
  • E. George
    George is a masculine given name of Greek origin, commonly used in English-speaking countries and borne by numerous historical and contemporary figures.
  • 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_69bd443aa1f88190abb992d138f2cf42 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7450312881908d4e3576ca65f7fb completed March 20, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea48cc7b88190a9ea43f79b0a0cf0 completed March 21, 2026, 2 p.m.
NEDg Description generation batch_69bea654fa8881908a50be410d4ea7d5 completed March 21, 2026, 2:08 p.m.
NED2 Entity disambiguation (via description) batch_69bea6ad303481909c41af9a4e002e0b completed March 21, 2026, 2:09 p.m.
Created at: March 20, 2026, 1:38 p.m.