Triple

T19128721
Position Surface form Disambiguated ID Type / Status
Subject Orator Shafer E468256 entity
Predicate givenName P17 FINISHED
Object George
George is the given name of 19th-century American baseball player Orator Shafer.
E1359304 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: [Orator Shafer, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [Orator Shafer, givenName, George]
  • A. George
    George is the given name of George Habash, the Palestinian Christian physician and founder of the Popular Front for the Liberation of Palestine.
  • B. George
    George is a supporting character in the romantic comedy film "27 Dresses," serving as a colleague and love interest within the story’s central wedding-planning world.
  • C. George
    George is the given first name of the American gangster Bugs Moran, a prominent Prohibition-era mobster in Chicago.
  • D. George
    George is the given name of the British historian George Macaulay Trevelyan, known for his influential works on English and Italian history.
  • E. George
    George is the given name of George North, 3rd Earl of Guilford, a British peer from the late 18th and early 19th centuries.
  • 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: [Orator Shafer, givenName, George]
Generated description
George is the given name of 19th-century American baseball player Orator Shafer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: George
Target entity description: George is the given name of 19th-century American baseball player Orator Shafer.
  • A. George
    George is the given first name of American Major League Baseball pitcher Lefty Tyler, who played in the early 20th century.
  • 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 W. Norris, a prominent early 20th-century American politician known for his progressive reforms and long service in the U.S. Congress.
  • D. George
    George is the first name of Hall of Fame baseball player Ken Griffey Jr., one of Major League Baseball’s most celebrated outfielders.
  • E. George
    George is the given name of George Rogers Clark Todd, a 19th-century American physician and Confederate surgeon during the Civil War.
  • 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_69d8dd0796a48190b34ce4cd9d3f3be5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3cf8d348190b27fc7d7d39f46f1 completed April 20, 2026, 8:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05e671f2988190a74d53989124026b completed May 14, 2026, 3:12 p.m.
NEDg Description generation batch_6a05e9406ba48190a50f4ea6b413e1f4 completed May 14, 2026, 3:24 p.m.
NED2 Entity disambiguation (via description) batch_6a05e9c0d35081909b6ce3c287af5d5f completed May 14, 2026, 3:26 p.m.
Created at: April 10, 2026, 12:05 p.m.